Time-Series Signals of Affect and Neural Dynamics with Technology to Identify Depression Risk

aan het Rot, M., Hogenelst, K., & Schoevers, R. A. (2012). Mood disorders in everyday life: a systematic review of

experience sampling and ecological momentary assessment studies. Clinical psychology review, 32(6),

-523. https://doi.org/10.1016/j.cpr.2012.05.007

Acharya, U. R., Oh, S. L., Hagiwara, Y., Tan, J. H., Adeli, H., & Subha, D. P. (2018). Automated EEG-based

screening of depression using deep convolutional neural network. Computer methods and programs in

biomedicine, 161, 103-113. https://doi.org/10.1016/j.cmpb.2018.04.012

Ahern, G. L., & Schwartz, G. E. (1985). Differential lateralization for positive and negative emotion in the human

brain: EEG spectral analysis. Neuropsychologia, 23(6), 745-755.

https://doi.org/10.1016/0028-3932(85)90081-8

American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.).

https://doi.org/10.1176/appi.books.9780890425596

American Psychiatric Association. (2022). The App Evaluation Model. Www.psychiatry.org.

https://www.psychiatry.org/psychiatrists/practice/mental-health-apps/the-app-evaluation-model

ASPE. (1996, August 20). Health Insurance Portability and Accountability Act of 1996. ASPE.

https://aspe.hhs.gov/reports/health-insurance-portability-accountability-act-1996

Badcock, N. A., Mousikou, P., Mahajan, Y., De Lissa, P., Thie, J., & McArthur, G. (2013). Validation of the Emotiv

EPOC® EEG gaming system for measuring research quality auditory ERPs. PeerJ, 1, e38.

https://doi.org/10.7717/peerj.38

Bakker, D., & Rickard, N. (2019). Engagement with a cognitive behavioural therapy mobile phone app predicts

changes in mental health and wellbeing: MoodMission. Australian Psychologist, 54(4), 245-260.

https://doi.org/10.1111/ap.12383

Barry, R. J., Clarke, A. R., Johnstone, S. J., Magee, C. A., & Rushby, J. A. (2007). EEG differences between

eyes-closed and eyes-open resting conditions. Clinical neurophysiology, 118(12), 2765-2773.

https://doi.org/10.1016/j.clinph.2007.07.028

Beck, A. T., Ward, C. H., Mendelson, M., Mock, J., & Erbaugh, J. (1961). An inventory for measuring depression.

Archives of general psychiatry, 4(6), 561-571. https://doi.org/10.1001/archpsyc.1961.01710120031004

Beck, A., Crain, A. L., Solberg, L. I., Unützer, J., Glasgow, R. E., Maciosek, M. V., & Whitebird, R. (2011). Severity

of depression and magnitude of productivity loss. The Annals of Family Medicine, 9(4), 305-311.

https://doi.org/10.1370/afm.1260

Bos, E. H., de Jonge, P., & Cox, R. F. (2019). Affective variability in depression: Revisiting the inertia–instability

paradox. British Journal of Psychology, 110(4), 814-827. https://doi.org/10.1111/bjop.12372

Bosley, H. G., Soyster, P. D., & Fisher, A. J. (2019). Affect dynamics as predictors of symptom severity and

treatment response in mood and anxiety disorders: Evidence for specificity. Journal for Person-Oriented

Research, 5(2), 101. https://doi.org/10.17505/jpor.2019.09

Burchert, S., Kerber, A., Zimmermann, J., & Knaevelsrud, C. (2021). Screening accuracy of a 14-day smartphone

ambulatory assessment of depression symptoms and mood dynamics in a general population sample:

comparison with the PHQ-9 depression screening. Plos one, 16(1), e0244955.

https://doi.org/10.1371/journal.pone.0244955

Byambasuren, O., Beller, E., Hoffmann, T., & Glasziou, P. (2020). Barriers to and facilitators of the prescription of

mHealth apps in Australian general practice: qualitative study. JMIR mHealth and uHealth, 8(7), e17447.

https://doi.org/10.2196/17447

Carswell, K., Harper-Shehadeh, M., Watts, S., van’t Hof, E., Abi Ramia, J., Heim, E., ... & van Ommeren, M.

(2018). Step-by-Step: a new WHO digital mental health intervention for depression. Mhealth, 4.

https://doi.org/10.21037/mhealth.2018.08.01

Chachamovich, E., Stefanello, S., Botega, N., & Turecki, G. (2009). Which are the recent clinical findings regarding

the association between depression and suicide?. Brazilian Journal of Psychiatry, 31, S18-S25.

https://doi.org/10.1590/s1516-44462009000500004

Chow, S. M., Ram, N., Boker, S. M., Fujita, F., & Clore, G. (2005). Emotion as a thermostat: representing emotion

regulation using a damped oscillator model. Emotion, 5(2), 208. https://doi.org/10.1037/1528-3542.5.2.208

Christianson, S. A., Saisa, J., Garvill, J., & Silfvenius, H. (1993). Hemisphere inactivation and mood-state changes.

Brain and Cognition, 23(2), 127-144. https://doi.org/10.1006/brcg.1993.1051

Coan, J. A., & Allen, J. J. (2004). Frontal EEG asymmetry as a moderator and mediator of emotion. Biological

psychology, 67(1-2), 7-50. https://doi.org/10.1016/j.biopsycho.2004.03.002

Colla, J., Buka, S., Harrington, D., & Murphy, J. M. (2006). Depression and modernization. Social psychiatry and

psychiatric epidemiology, 41(4), 271-279. https://doi.org/10.1007/s00127-006-0032-8

Crowe, E., Daly, M., Delaney, L., Carroll, S., & Malone, K. M. (2019). The intra-day dynamics of affect,

self-esteem, tiredness, and suicidality in Major Depression. Psychiatry Research, 279, 98-108.

https://doi.org/10.1016/j.psychres.2018.02.032

Csikszentmihalyi, M., & Larson, R. (1987). Validity and reliability of the experience-sampling method. In Flow and

the foundations of positive psychology (pp. 35-54). Springer, Dordrecht.

https://doi.org/10.1007/978-94-017-9088-8_3

Csikszentmihalyi, M., & Seligman, M. (2000). Positive psychology. American psychologist, 55(1), 5-14.

Curtiss, J. E., Mischoulon, D., Fisher, L. B., Cusin, C., Fedor, S., Picard, R. W., & Pedrelli, P. (2021). Rising early

warning signals in affect associated with future changes in depression: a dynamical systems approach.

Psychological Medicine, 1-9. https://doi.org/10.1017/S0033291721005183

Davidson, R. J., Pizzagalli, D. A., & Nitschke, J. B. (2009). Representation and regulation of emotion in depression:

Perspectives from af ective neuroscience. The Guilford Press.

Davidson, R. J. (1988). EEG measures of cerebral asymmetry: Conceptual and methodological issues. International

journal of neuroscience, 39(1-2), 71-89. https://doi.org/10.3109/00207458808985694

Debener, S., Minow, F., Emkes, R., Gandras, K., & De Vos, M. (2012). How about taking a low‐cost, small, and

wireless EEG for a walk?. Psychophysiology, 49(11), 1617-1621.

https://doi.org/10.1111/j.1469-8986.2012.01471.x

de Jonge, M., Dekker, J. J. M., Kikkert, M. J., Peen, J., van Rijsbergen, G. D., & Bockting, C. L. H. (2017). The role

of affect in predicting depressive symptomatology in remitted recurrently depressed patients. Journal of

Af ective Disorders, 210, 66-71. https://doi.org/10.1016/j.jad.2016.12.015

Eaton, L. G., & Funder, D. C. (2001). Emotional experience in daily life: valence, variability, and rate of change.

Emotion, 1(4), 413. https://doi.org/10.1037/1528-3542.1.4.413

Ebner-Priemer, U. W., & Trull, T. J. (2009). Ecological momentary assessment of mood disorders and mood

dysregulation. Psychological assessment, 21(4), 463. https://doi.org/10.1037/a0017075

Eid, M., & Diener, E. (1999). Intraindividual variability in affect: Reliability, validity, and personality correlates.

Journal of personality and social psychology, 76(4), 662. https://doi.org/10.1037/0022-3514.76.4.662

Ellsworth, P. C., & Scherer, K. R. (2003). Appraisal processes in emotion. Oxford University Press.

Erbas, Y., Ceulemans, E., Lee Pe, M., Koval, P., & Kuppens, P. (2014). Negative emotion differentiation: Its

personality and well-being correlates and a comparison of different assessment methods. Cognition and

emotion, 28(7), 1196-1213. https://doi.org/10.1080/02699931.2013.875890

Fava, G. A., Rafanelli, C., Grandi, S., Conti, S., & Belluardo, P. (1998). Prevention of recurrent depression with

cognitive behavioral therapy: preliminary findings. Archives of general psychiatry, 55(9), 816-820.

https://doi.org/10.1001/archpsyc.55.9.816

Fawcett, J. (1993). The morbidity and mortality of clinical depression. International clinical psychopharmacology.

https://doi.org/10.1097/00004850-199300840-00002

Fingelkurts, A. A., Fingelkurts, A. A., Rytsälä, H., Suominen, K., Isometsä, E., & Kähkönen, S. (2006).

Composition of brain oscillations in ongoing EEG during major depression disorder. Neuroscience

research, 56(2), 133-144. https://doi.org/10.1016/j.neures.2006.06.006

Fleming, T., Bavin, L., Lucassen, M., Stasiak, K., Hopkins, S., & Merry, S. (2018). Beyond the trial: systematic

review of real-world uptake and engagement with digital self-help interventions for depression, low mood,

or anxiety. Journal of medical Internet research, 20(6), e9275. https://doi.org/10.2196/jmir.9275

Flor-Henry, P., Lind, J. C., & Koles, Z. J. (2004). A source-imaging (low-resolution electromagnetic tomography)

study of the EEGs from unmedicated males with depression. Psychiatry Research: Neuroimaging, 130(2),

-207. https://doi.org/10.1016/j.pscychresns.2003.08.006

Frijda, N. H., Kuipers, P., & Ter Schure, E. (1989). Relations among emotion, appraisal, and emotional action

readiness. Journal of personality and social psychology, 57(2), 212.

https://doi.org/10.1037/0022-3514.57.2.212

Garrido, S., Millington, C., Cheers, D., Boydell, K., Schubert, E., Meade, T., & Nguyen, Q. V. (2019). What works

and what doesn’t work? A systematic review of digital mental health interventions for depression and

anxiety in young people. Frontiers in psychiatry, 10, 759. https://doi.org/10.3389/fpsyt.2019.00759

Geschwind, N., Nicolson, N. A., Peeters, F., van Os, J., Barge-Schaapveld, D., & Wichers, M. (2011). Early

improvement in positive rather than negative emotion predicts remission from depression after

pharmacotherapy. European Neuropsychopharmacology, 21(3), 241-247.

https://doi.org/10.1016/j.euroneuro.2010.11.004

Geschwind, N., Peeters, F., Drukker, M., van Os, J., & Wichers, M. (2011). Mindfulness training increases

momentary positive emotions and reward experience in adults vulnerable to depression: a randomized

controlled trial. Journal of consulting and clinical psychology, 79(5), 618.

https://doi.org/10.1037/a0024595

Gotlib, I. H. (1998). EEG alpha asymmetry, depression, and cognitive functioning. Cognition & Emotion, 12(3),

-478. https://doi.org/10.1080/026999398379673

Greco, C., Matarazzo, O., Cordasco, G., Vinciarelli, A., Callejas, Z., & Esposito, A. (2021). Discriminative power of

EEG-based biomarkers in major depressive disorder: A systematic review. IEEE Access.

https://doi.org/10.1109/ACCESS.2021.3103047

Grin-Yatsenko, V. A., Baas, I., Ponomarev, V. A., & Kropotov, J. D. (2009). EEG power spectra at early stages of

depressive disorders. Journal of clinical neurophysiology, 26(6), 401-406.

https://doi.org/10.1097/WNP.0b013e3181c298fe

Grin-Yatsenko, V. A., Baas, I., Ponomarev, V. A., & Kropotov, J. D. (2010). Independent component approach to the

analysis of EEG recordings at early stages of depressive disorders. Clinical Neurophysiology, 121(3),

-289. https://doi.org/10.1016/j.clinph.2009.11.015

Gruber, J., Kogan, A., Quoidbach, J., & Mauss, I. B. (2013). Happiness is best kept stable: positive emotion

variability is associated with poorer psychological health. Emotion, 13(1), 1.

https://doi.org/10.1037/a0030262

Gu, X., Cao, Z., Jolfaei, A., Xu, P., Wu, D., Jung, T. P., & Lin, C. T. (2021). EEG-based brain-computer interfaces

(BCIs): A survey of recent studies on signal sensing technologies and computational intelligence

approaches and their applications. IEEE/ACM transactions on computational biology and bioinformatics,

(5), 1645-1666. https://doi.org/10.1109/TCBB.2021.3052811

Hallensleben, N., Spangenberg, L., Forkmann, T., Rath, D., Hegerl, U., Kersting, A., ... & Glaesmer, H. (2018).

Investigating the dynamics of suicidal ideation: Preliminary findings from a study using ecological

momentary assessments in psychiatric inpatients. Crisis: The Journal of Crisis Intervention and Suicide

Prevention, 39(1), 65. https://doi.org/10.1027/0227-5910/a000464

Hammond, D. C. (2011). What is neurofeedback: An update. Journal of Neurotherapy, 15(4), 305-336.

https://doi.org/10.1080/10874208.2011.623090

Hansson, L. (2002). Quality of life in depression and anxiety. International Review of Psychiatry, 14(3), 185-189.

https://doi.org/10.1080/09540260220144966

Henriques, J. B., & Davidson, R. J. (1991). Left frontal hypoactivation in depression. Journal of abnormal

psychology, 100(4), 535. https://doi.org/10.1037//0021-843x.100.4.535

Hidaka, B. H. (2012). Depression as a disease of modernity: explanations for increasing prevalence. Journal of

af ective disorders, 140(3), 205-214. https://doi.org/10.1016/j.jad.2011.12.036

Hoemann, K., Barrett, L. F., & Quigley, K. S. (2021). Emotional granularity increases with intensive ambulatory

assessment: Methodological and individual factors influence how much. Frontiers in psychology, 12,

https://doi.org/10.3389/fpsyg.2021.704125

Holmes, A. J., Lee, P. H., Hollinshead, M. O., Bakst, L., Roffman, J. L., Smoller, J. W., & Buckner, R. L. (2012).

Individual differences in amygdala-medial prefrontal anatomy link negative affect, impaired social

functioning, and polygenic depression risk. Journal of Neuroscience, 32(50), 18087-18100.

https://doi.org/10.1523/JNEUROSCI.2531-12.2012

Hosseinifard, B., Moradi, M. H., & Rostami, R. (2013). Classifying depression patients and normal subjects using

machine learning techniques and nonlinear features from EEG signal. Computer methods and programs in

biomedicine, 109(3), 339-345. https://doi.org/10.1016/j.cmpb.2012.10.008

Houben, M., Van Den Noortgate, W., & Kuppens, P. (2015). The relation between short-term emotion dynamics and

psychological well-being: A meta-analysis. Psychological bulletin, 141(4), 901.

https://doi.org/10.1037/a0038822

Jahng, S., Wood, P. K., & Trull, T. J. (2008). Analysis of affective instability in ecological momentary assessment:

Indices using successive difference and group comparison via multilevel modeling. Psychological methods,

(4), 354. https://doi.org/10.1037/a0014173

Jaworska, N., Blier, P., Fusee, W., & Knott, V. (2012). Alpha power, alpha asymmetry and anterior cingulate cortex

activity in depressed males and females. Journal of psychiatric research, 46(11), 1483-1491.

https://doi.org/10.1016/j.jpsychires.2012.08.003

Kaiser, J., & Lutzenberger, W. (2005). Human gamma-band activity: a window to cognitive processing.

Neuroreport, 16(3), 207-211. https://doi.org/10.1097/00001756-200502280-00001

Kane, J., Cavanagh, J. F., & Dillon, D. G. (2019). Reduced theta power during memory retrieval in depressed adults.

Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 4(7), 636-643.

https://doi.org/10.1016/j.bpsc.2019.03.004

Kashdan, T. B., Barrett, L. F., & McKnight, P. E. (2015). Unpacking emotion differentiation: Transforming

unpleasant experience by perceiving distinctions in negativity. Current Directions in Psychological Science,

(1), 10-16. https://doi.org/10.1177/0963721414550708

Kendler, K. S., Prescott, C. A., Myers, J., & Neale, M. C. (2003). The structure of genetic and environmental risk

factors for common psychiatric and substance use disorders in men and women. Archives of general

psychiatry, 60(9), 929-937. https://doi.org/10.1001/archpsyc.60.9.929

Kessler, R. C. (2012). The costs of depression. Psychiatric Clinics, 35(1), 1-14.

https://doi.org/10.1016/j.psc.2011.11.005

Knott, V., Mahoney, C., Kennedy, S., & Evans, K. (2001). EEG power, frequency, asymmetry and coherence in male

depression. Psychiatry Research: Neuroimaging, 106(2), 123-140.

https://doi.org/10.1016/s0925-4927(00)00080-9

Koenigsberg, H. W. (2010). Affective instability: toward an integration of neuroscience and psychological

perspectives. Journal of personality disorders, 24(1), 60. https://doi.org/10.1521/pedi.2010.24.1.60

Koval, P., Kuppens, P., Allen, N. B., & Sheeber, L. (2012). Getting stuck in depression: The roles of rumination and

emotional inertia. Cognition & emotion, 26(8), 1412-1427. https://doi.org/10.1080/02699931.2012.667392

Koval, P., Pe, M. L., Meers, K., & Kuppens, P. (2013). Affect dynamics in relation to depressive symptoms:

variable, unstable or inert?. Emotion, 13(6), 1132. https://doi.org/10.1037/a0033579

Kullar, M., Carter, S., Hitchcock, C., Whittaker, S., Wright, A. G., & Dalgleish, T. (2023). Patterns of

emotion-network dynamics are orthogonal to mood disorder status: An experience sampling investigation.

Emotion. https://doi.org/10.1037/emo0001245

Kuppens, P., Allen, N. B., & Sheeber, L. B. (2010). Emotional inertia and psychological maladjustment.

Psychological science, 21(7), 984-991. https://doi.org/10.1177/0956797610372634

Kuppens, P., Sheeber, L. B., Yap, M. B., Whittle, S., Simmons, J. G., & Allen, N. B. (2012). Emotional inertia

prospectively predicts the onset of depressive disorder in adolescence. Emotion, 12(2), 283.

https://doi.org/10.1037/a0025046

Kuppens, P. (2015). It’s about time: A special section on affect dynamics. Emotion Review, 7(4), 297-300.

https://doi.org/10.1177/1754073915590947

Kuyken, W., Warren, F. C., Taylor, R. S., Whalley, B., Crane, C., Bondolfi, G., ... & Dalgleish, T. (2016). Efficacy of

mindfulness-based cognitive therapy in prevention of depressive relapse: an individual patient data

meta-analysis from randomized trials. JAMA psychiatry, 73(6), 565-574.

https://doi.org/10.1001/jamapsychiatry.2016.0076

Larsen, R. J. (2000). Toward a science of mood regulation. Psychological inquiry, 11(3), 129-141.

https://doi.org/10.1207/S15327965PLI1103_01

Leichsenring, F., Abbass, A., Hilsenroth, M. J., Luyten, P., Munder, T., Rabung, S., & Steinert, C. (2018). “Gold

standards,” plurality and monocultures: The need for diversity in psychotherapy. Frontiers in psychiatry, 9,

https://doi.org/10.3389/fpsyt.2018.00159

Lerner, D., Adler, D. A., Chang, H., Lapitsky, L., Hood, M. Y., Perissinotto, C., ... & Rogers, W. H. (2004).

Unemployment, job retention, and productivity loss among employees with depression. Psychiatric

Services, 55(12), 1371-1378. https://doi.org/10.1176/appi.ps.55.12.1371

Mahato, S., & Paul, S. (2019). Electroencephalogram (EEG) signal analysis for diagnosis of major depressive

disorder (MDD): a review. Nanoelectronics, Circuits and Communication Systems, 323-335.

http://dx.doi.org/10.1007/978-981-13-0776-8_30

Marshall, J. M., Dunstan, D. A., & Bartik, W. (2019). The digital psychiatrist: in search of evidence-based apps for

anxiety and depression. Frontiers in Psychiatry, 10, 831. https://doi.org/10.3389/fpsyt.2019.00831

Martin, E. A., Siegle, G. J., Steinhauer, S. R., & Condray, R. (2019). Timing matters in elaborative processing of

positive stimuli: Gamma band reactivity in schizophrenia compared to depression and healthy adults.

Schizophrenia research, 204, 111-119. https://doi.org/10.1016/j.schres.2018.08.008

Marvel, C. L., & Paradiso, S. (2004). Cognitive and neurological impairment in mood disorders. Psychiatric Clinics,

(1), 19-36. https://doi.org/10.1016/s0193-953x(03)00106-0

Marwaha, S., He, Z., Broome, M., Singh, S. P., Scott, J., Eyden, J., & Wolke, D. (2014). How is affective instability

defined and measured? A systematic review. Psychological medicine, 44(9), 1793-1808.

https://doi.org/10.1017/s0033291713002407

McLoughlin, G., Makeig, S., & Tsuang, M. T. (2014). In search of biomarkers in psychiatry: EEG‐based measures

of brain function. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics, 165(2),

-121. https://doi.org/10.1002/ajmg.b.32208

Melek, M., Manshouri, N., & KAYIKÇIOĞLU, T. (2020). Low-cost brain-computer interface using the emotiv epoc

headset based on rotating vanes. Traitement du Signal, 37(5). https://doi.org/10.18280/ts.370516

Minaeva, O., Booij, S. H., Lamers, F., Antypa, N., Schoevers, R. A., Wichers, M., & Riese, H. (2020). Level and

timing of physical activity during normal daily life in depressed and non-depressed individuals.

Translational psychiatry, 10(1), 1-11. https://doi.org/10.1038/s41398-020-00952-w

Mohr, D. C., Tomasino, K. N., Lattie, E. G., Palac, H. L., Kwasny, M. J., Weingardt, K., ... & Schueller, S. M.

(2017). IntelliCare: an eclectic, skills-based app suite for the treatment of depression and anxiety. Journal

of medical Internet research, 19(1), e6645. https://doi.org/10.2196/jmir.6645

Mummah, S. A., Robinson, T. N., King, A. C., Gardner, C. D., & Sutton, S. (2016). IDEAS (Integrate, Design,

Assess, and Share): a framework and toolkit of strategies for the development of more effective digital

interventions to change health behavior. Journal of medical Internet research, 18(12), e5927.

https://doi.org/10.2196/jmir.5927

Mumtaz, W., Malik, A. S., Yasin, M. A. M., & Xia, L. (2015). Review on EEG and ERP predictive biomarkers for

major depressive disorder. Biomedical Signal Processing and Control, 22, 85-98.

https://doi.org/10.1016/j.bspc.2015.07.003

Mumtaz, W., Xia, L., Ali, S. S. A., Yasin, M. A. M., Hussain, M., & Malik, A. S. (2017). Electroencephalogram

(EEG)-based computer-aided technique to diagnose major depressive disorder (MDD). Biomedical Signal

Processing and Control, 31, 108-115. https://doi.org/10.1016/j.bspc.2016.07.006

Murphy, O. W., Hoy, K. E., Wong, D., Bailey, N. W., Fitzgerald, P. B., & Segrave, R. A. (2019). Individuals with

depression display abnormal modulation of neural oscillatory activity during working memory encoding

and maintenance. Biological Psychology, 148, 107766. https://doi.org/10.1016/j.biopsycho.2019.107766

Neary, M., & Schueller, S. M. (2018). State of the field of mental health apps. Cognitive and Behavioral Practice,

(4), 531-537. https://doi.org/10.1016/j.cbpra.2018.01.002

Newman, M. G., Szkodny, L. E., Llera, S. J., & Przeworski, A. (2011). A review of technology-assisted self-help

and minimal contact therapies for anxiety and depression: is human contact necessary for therapeutic

efficacy?. Clinical psychology review, 31(1), 89-103. https://doi.org/10.1016/j.cpr.2010.09.008

Newson, J. J., & Thiagarajan, T. C. (2019). EEG frequency bands in psychiatric disorders: a review of resting state

studies. Frontiers in human neuroscience, 12, 521. https://doi.org/10.3389/fnhum.2018.00521

One Mind PsyberGuide. (2016). App Guide | PsyberGuide. One Mind PsyberGuide.

https://onemindpsyberguide.org/apps/

Ormel, J., Von Korff, M., Van den Brink, W., Katon, W., Brilman, E., & Oldehinkel, T. (1993). Depression, anxiety,

and social disability show synchrony of change in primary care patients. American Journal of Public

Health, 83(3), 385-390. https://doi.org/10.2105/ajph.83.3.385

Otte, C., Gold, S. M., Penninx, B. W., Pariante, C. M., Etkin, A., Fava, M., ... & Schatzberg, A. F. (2016). Major

depressive disorder. Nature reviews Disease primers, 2(1), 1-20. https://doi.org/10.1038/nrdp.2016.65

Oud, M., De Winter, L., Vermeulen-Smit, E., Bodden, D., Nauta, M., Stone, L., ... & Stikkelbroek, Y. (2019).

Effectiveness of CBT for children and adolescents with depression: A systematic review and

meta-regression analysis. European psychiatry, 57, 33-45. https://doi.org/10.1016/j.eurpsy.2018.12.008

Parks, A. C., Williams, A. L., Tugade, M. M., Hokes, K. E., Honomichl, R. D., & Zilca, R. D. (2018). Testing a

scalable web and smartphone based intervention to improve depression, anxiety, and resilience: A

randomized controlled trial. International Journal of Wellbeing, 8(2). https://doi.org/10.5502/ijw.v8i2.745

Peeters, F., Berkhof, J., Delespaul, P., Rottenberg, J., & Nicolson, N. A. (2006). Diurnal mood variation in major

depressive disorder. Emotion, 6(3), 383. https://doi.org/10.1037/1528-3542.6.3.383

Pyne, J. M., Patterson, T. L., Kaplan, R. M., Gillin, J. C., Koch, W. L., & Grant, I. (1997). Assessment of the quality

of life of patients with major depression. Psychiatric services. https://doi.org/10.1176/ps.48.2.224

Quiroga, C. V., Janosz, M., Bisset, S., & Morin, A. J. (2013). Early adolescent depression symptoms and school

dropout: Mediating processes involving self-reported academic competence and achievement. Journal of

Educational Psychology, 105(2), 552. https://doi.org/10.1037/a0031524

Ross, S., Bossis, A., Guss, J., Agin-Liebes, G., Malone, T., Cohen, B., ... & Schmidt, B. L. (2016). Rapid and

sustained symptom reduction following psilocybin treatment for anxiety and depression in patients with

life-threatening cancer: a randomized controlled trial. Journal of psychopharmacology, 30(12), 1165-1180.

https://doi.org/10.1177/0269881116675512

Rucci, P., Frank, E., Calugi, S., Miniati, M., Benvenuti, A., Wallace, M., ... & Cassano, G. B. (2011). Incidence and

predictors of relapse during continuation treatment of major depression with SSRI, interpersonal

psychotherapy, or their combination. Depression and Anxiety, 28(11), 955-962.

https://doi.org/10.1002/da.20894

Schaffer, C. E., Davidson, R. J., & Saron, C. (1983). Frontal and parietal electroencephalogram asymmetry in

depressed and nondepressed subjects. Biological psychiatry.

Scheffer, M., Bascompte, J., Brock, W. A., Brovkin, V., Carpenter, S. R., Dakos, V., ... & Sugihara, G. (2009).

Early-warning signals for critical transitions. Nature, 461(7260), 53-59.

https://doi.org/10.1038/nature08227

Schwerdtfeger, A., & Friedrich-Mai, P. (2009). Social interaction moderates the relationship between depressive

mood and heart rate variability: evidence from an ambulatory monitoring study. Health Psychology, 28(4),

https://doi.org/10.1037/a0014664

Segal, Z., Williams, M., & Teasdale, J. (2018). Mindfulness-based cognitive therapy for depression. Guilford

Publications.

Segrave, R. A., Thomson, R. H., Cooper, N. R., Croft, R. J., Sheppard, D. M., & Fitzgerald, P. B. (2010). Upper

alpha activity during working memory processing reflects abnormal inhibition in major depression. Journal

of af ective disorders, 127(1-3), 191-198. https://doi.org/10.1016/j.jad.2010.05.022

Seguin, M., Lesage, A., Turecki, G., Bouchard, M., Chawky, N., Tremblay, N., ... & Guy, A. (2007). Life trajectories

and burden of adversity: mapping the developmental profiles of suicide mortality. Psychological medicine,

(11), 1575-1583. https://doi.org/10.1017/s0033291707000955

Shen, N., Levitan, M. J., Johnson, A., Bender, J. L., Hamilton-Page, M., Jadad, A. A. R., & Wiljer, D. (2015).

Finding a depression app: a review and content analysis of the depression app marketplace. JMIR mHealth

and uHealth, 3(1), e3713. https://doi.org/10.2196/mhealth.3713

Shephard, R. J., & Rode, A. (1996). The Health Consequences of'Modernisation': Evidence from Circumpolar

Peoples (Vol. 17). Cambridge University Press. https://doi.org/10.1017/CBO9780511983726

Siegle, G. J., Condray, R., Thase, M. E., Keshavan, M., & Steinhauer, S. R. (2010). Sustained gamma-band EEG

following negative words in depression and schizophrenia. International Journal of Psychophysiology,

(2), 107-118. https://doi.org/10.1016/j.ijpsycho.2008.04.008

Smidt, K. E., & Suvak, M. K. (2015). A brief, but nuanced, review of emotional granularity and emotion

differentiation research. Current Opinion in Psychology, 3, 48-51.

https://doi.org/10.1016/j.copsyc.2015.02.007

Smit, D. J. A., Posthuma, D., Boomsma, D. I., & De Geus, E. J. C. (2007). The relation between frontal EEG

asymmetry and the risk for anxiety and depression. Biological psychology, 74(1), 26-33.

https://doi.org/10.1016/j.biopsycho.2006.06.002

Sobocki, P., Jönsson, B., Angst, J., & Rehnberg, C. (2006). Cost of depression in Europe. Journal of Mental Health

Policy and Economics.

Solomon, D. A., Keller, M. B., Leon, A. C., Mueller, T. I., Lavori, P. W., Shea, M. T., ... & Endicott, J. (2000).

Multiple recurrences of major depressive disorder. American Journal of Psychiatry, 157(2), 229-233.

https://doi.org/10.1176/appi.ajp.157.2.229

Spironelli, C., Maffei, A., Romeo, Z., Piazzon, G., Padovan, G., Magnolfi, G., ... & Angrilli, A. (2020). Evidence of

language-related left hypofrontality in Major Depression: An EEG Beta band study. Scientific reports,

(1), 1-12. https://doi.org/10.1038/s41598-020-65168-w

Starr, L. R., Hershenberg, R., Li, Y. I., & Shaw, Z. A. (2017). When feelings lack precision: Low positive and

negative emotion differentiation and depressive symptoms in daily life. Clinical Psychological Science,

(4), 613-631. https://doi.org/10.1177/2167702617694657

Statista. (2020, August 20). Number of Smartphone Users Worldwide 2014-2020 | Statista. Statista; Statista.

https://www.statista.com/statistics/330695/number-of-smartphone-users-worldwide/

Thibodeau, R., Jorgensen, R. S., & Kim, S. (2006). Depression, anxiety, and resting frontal EEG asymmetry: a

meta-analytic review. Journal of abnormal psychology, 115(4), 715.

https://doi.org/10.1037/0021-843X.115.4.715

Thompson, R. J., Mata, J., Jaeggi, S. M., Buschkuehl, M., Jonides, J., & Gotlib, I. H. (2012). The everyday

emotional experience of adults with major depressive disorder: Examining emotional instability, inertia,

and reactivity. Journal of abnormal psychology, 121(4), 819. https://doi.org/10.1037/a0027978

Thompson, R. J., Boden, M. T., & Gotlib, I. H. (2017). Emotional variability and clarity in depression and social

anxiety. Cognition and Emotion, 31(1), 98-108. https://doi.org/10.1080/02699931.2015.1084908

Tomarken, A. J., Davidson, R. J., & Henriques, J. B. (1990). Resting frontal brain asymmetry predicts affective

responses to films. Journal of personality and social psychology, 59(4), 791.

https://doi.org/10.1037//0022-3514.59.4.791

Torous, J., Firth, J., Huckvale, K., Larsen, M. E., Cosco, T. D., Carney, R., ... & Christensen, H. (2018). The

emerging imperative for a consensus approach toward the rating and clinical recommendation of mental

health apps. The Journal of nervous and mental disease, 206(8), 662-666.

https://doi.org/10.1097/NMD.0000000000000864

Trull, T. J., & Ebner-Priemer, U. (2013). Ambulatory assessment. Annual review of clinical psychology, 9, 151.

https://doi.org/10.1146/annurev-clinpsy-050212-185510

Trull, T. J., & Ebner-Priemer, U. W. (2009). Using experience sampling methods/ecological momentary assessment

(ESM/EMA) in clinical assessment and clinical research: introduction to the special section.

https://doi.org/10.1037/a0017653

Trull, T. J., Lane, S. P., Koval, P., & Ebner-Priemer, U. W. (2015). Affective dynamics in psychopathology. Emotion

Review, 7(4), 355-361. https://doi.org/10.1177/1754073915590617

Trull, T. J., Solhan, M. B., Tragesser, S. L., Jahng, S., Wood, P. K., Piasecki, T. M., & Watson, D. (2008). Affective

instability: measuring a core feature of borderline personality disorder with ecological momentary

assessment. Journal of abnormal psychology, 117(3), 647. https://doi.org/10.1037/a0012532

Tugade, M. M., Fredrickson, B. L., & Feldman Barrett, L. (2004). Psychological resilience and positive emotional

granularity: Examining the benefits of positive emotions on coping and health. Journal of personality,

(6), 1161-1190. https://doi.org/10.1111/j.1467-6494.2004.00294.x

Turecki, G., Brent, D. A., Gunnell, D., O’Connor, R. C., Oquendo, M. A., Pirkis, J., & Stanley, B. H. (2019). Suicide

and suicide risk. Nature reviews Disease primers, 5(1), 1-22. https://doi.org/10.1038/s41572-019-0121-0

Twomey, C., & O’Reilly, G. (2017). Effectiveness of a freely available computerised cognitive behavioural therapy

programme (MoodGYM) for depression: Meta-analysis. Australian & New Zealand Journal of Psychiatry,

(3), 260-269. https://doi.org/10.1177/0004867416656258

van de Leemput, I. A., Wichers, M., Cramer, A. O., Borsboom, D., Tuerlinckx, F., Kuppens, P., ... & Scheffer, M.

(2014). Critical slowing down as early warning for the onset and termination of depression. Proceedings of

the National Academy of Sciences, 111(1), 87-92. https://doi.org/10.1073/pnas.1312114110

Van der Gucht, K., Dejonckheere, E., Erbas, Y., Takano, K., Vandemoortele, M., Maex, E., ... & Kuppens, P. (2019).

An experience sampling study examining the potential impact of a mindfulness-based intervention on

emotion differentiation. Emotion, 19(1), 123. https://doi.org/10.1037/emo0000406

Van Der Vinne, N., Vollebregt, M. A., Van Putten, M. J., & Arns, M. (2017). Frontal alpha asymmetry as a

diagnostic marker in depression: Fact or fiction? A meta-analysis. Neuroimage: clinical, 16, 79-87.

https://doi.org/10.1016/j.nicl.2017.07.006

van Rijsbergen, G. D., Bockting, C. L., Berking, M., Koeter, M. W., & Schene, A. H. (2012). Can a one-item mood

scale do the trick? Predicting relapse over 5.5-years in recurrent depression.

https://doi.org/10.1371/journal.pone.0046796

van Rijsbergen, G. D., Bockting, C. L., Burger, H., Spinhoven, P., Koeter, M. W., Ruhé, H. G., ... & Schene, A. H.

(2013). Mood reactivity rather than cognitive reactivity is predictive of depressive relapse: a randomized

study with 5.5-year follow-up. Journal of Consulting and Clinical Psychology, 81(3), 508.

https://doi.org/10.1037/a0032223

Wells, K. B., Stewart, A., Hays, R. D., Burnam, M. A., Rogers, W., Daniels, M., ... & Ware, J. (1989). The

functioning and well-being of depressed patients: results from the Medical Outcomes Study. Jama, 262(7),

-919. https://doi.org/10.1001/jama.1989.03430070062031

Wichers, M., Geschwind, N., Jacobs, N., Kenis, G., Peeters, F., Derom, C., ... & van Os, J. (2009). Transition from

stress sensitivity to a depressive state: longitudinal twin study. The British Journal of Psychiatry, 195(6),

-503. https://doi.org/10.1192/bjp.bp.108.056853

Wichers, M., Myin-Germeys, I., Jacobs, N., Peeters, F., Kenis, G., Derom, C., ... & Van Os, J. (2007). Genetic risk

of depression and stress-induced negative affect in daily life. The British Journal of Psychiatry, 191(3),

-223. https://doi.org/10.1192/bjp.bp.106.032201

Wichers, M., Peeters, F., Geschwind, N., Jacobs, N., Simons, C. J. P., Derom, C., ... & Van Os, J. (2010). Unveiling

patterns of affective responses in daily life may improve outcome prediction in depression: a momentary

assessment study. Journal of af ective disorders, 124(1-2), 191-195.

https://doi.org/10.1016/j.jad.2009.11.010

Wichers, M., Peeters, F., Rutten, B. P., Jacobs, N., Derom, C., Thiery, E., ... & van Os, J. (2012). A time-lagged

momentary assessment study on daily life physical activity and affect. Health Psychology, 31(2), 135.

https://doi.org/10.1037/a0025688

Wichers, M., Smit, A. C., & Snippe, E. (2020). Early warning signals based on momentary affect dynamics can

expose nearby transitions in depression: a confirmatory single-subject time-series study. Journal for

Person-Oriented Research, 6(1), 1. https://doi.org/10.17505/jpor.2020.22042

Widdershoven, R. L., Wichers, M., Kuppens, P., Hartmann, J. A., Menne-Lothmann, C., Simons, C. J., &

Bastiaansen, J. A. (2019). Effect of self-monitoring through experience sampling on emotion differentiation

in depression. Journal of af ective disorders, 244, 71-77. https://doi.org/10.1016/j.jad.2018.10.092

World Health Organization. (2021). Suicide worldwide in 2019. Www.who.int.

https://www.who.int/publications/i/item/9789240026643

Wright, A. G., & Zimmermann, J. (2019). Applied ambulatory assessment: Integrating idiographic and nomothetic

principles of measurement. Psychological assessment, 31(12), 1467. https://doi.org/10.1037/pas0000685

Yan, S., Hosseinmardi, H., Kao, H. T., Narayanan, S., Lerman, K., & Ferrara, E. (2019, June). Estimating

individualized daily self-reported affect with wearable sensors. In 2019 IEEE International Conference on

Healthcare Informatics (ICHI) (pp. 1-9). IEEE. https://doi.org/10.1109/ICHI.2019.8904691