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Inferring Mood Instability on Social Media by Leveraging Ecological Momentary Assessments

Koustuv Saha, Larry Chan, Kaya De Barbaro, Gregory D. Abowd, Munmun De Choudhury
2017 Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies  
We propose a semi-supervised machine learning framework to combine small samples of data gathered through active sensing, with large-scale social media data to infer mood instability (MI) in individuals  ...  Active and passive sensing technologies are providing powerful mechanisms to track, model, and understand a range of health behaviors and well-being states.  ...  We especially thank Marie Le Pichon for her help with the IRB protocol, as well as in providing guidance on the privacy considerations of the study.  ... 
doi:10.1145/3130960 fatcat:ch2qnshq4bhp3idoyncr45qcya

A Survey of Passive Sensing in the Workplace [article]

Subigya Nepal, Gonzalo J. Martinez, Shayan Mirjafari, Koustuv Saha, Vedant Das Swain, Xuhai Xu, Pino G. Audia, Munmun De Choudhury, Anind K. Dey, Aaron Striegel, Andrew T. Campbell
2022 arXiv   pre-print
New passive sensing technology is emerging capable of assessing human behavior with the goal of promoting better cognitive and physical capabilities at work.  ...  In this article, we survey recent research on the use of passive sensing in the workplace to assess wellbeing and productivity of the workforce.  ...  We presented a survey of the most recent relevant studies demonstrating the current research trends and future potential of passive sensing technology in the workplace.  ... 
arXiv:2201.03074v1 fatcat:6xupuqnd7rgezbiopvxjg4dhey

Predicting Emotional State Using Behavioural Markers Derived from Passively Sensed Data: a Data-Driven Approach (Preprint)

Emese Sukei, Agnes Norbury, M. Mercedes Perez-Rodriguez, Pablo M. Olmos, Antonio Artés Rodríguez
2020 JMIR mHealth and uHealth  
These findings demonstrate the feasibility of designing machine learning models for predicting emotional states from mobile sensing data capable of dealing with heterogeneous data with large numbers of  ...  However, mobile sensed data are usually noisy and incomplete, with significant amounts of missing observations.  ...  Objectives This study focuses on applying machine learning algorithms to predict mood states based on passively sensed behavioral patterns.  ... 
doi:10.2196/24465 pmid:33749612 fatcat:mysmpi55unbj7llusywy3525wq

Digital Phenotyping in Bipolar Disorder: Which Integration with Clinical Endophenotypes and Biomarkers?

Laura Orsolini, Michele Fiorani, Umberto Volpe
2020 International Journal of Molecular Sciences  
Finally, digital phenotyping might potentially constitute a possible predictive marker for mood disorders.  ...  Moreover, a digital phenotyping approach may easily introduce and allow clinicians to perform a more personalized and patient-tailored diagnostic and therapeutic approach, in line with the framework of  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/ijms21207684 pmid:33081393 pmcid:PMC7589576 fatcat:eebadpk5zjdv3bcnylbxlazqim

Characterizing Affective Instability in Borderline Personality Disorder

Harold W. Koenigsberg, Philip D. Harvey, Vivian Mitropoulou, James Schmeidler, Antonia S. New, Marianne Goodman, Jeremy M. Silverman, Michael Serby, Frances Schopick, Larry J. Siever
2002 American Journal of Psychiatry  
The authors also examined the subjective intensity with which moods are experienced and the association between instability and intensity of affect.  ...  Method: In a group of 152 patients with personality disorders, subjective affective intensity and six dimensions of affective instability were measured.  ...  They found that patients with borderline personality disorder showed greater morning-to-evening mood variability and a more random distribution of morning moods than did patients with major depression  ... 
doi:10.1176/appi.ajp.159.5.784 pmid:11986132 fatcat:bdptzsgxs5endcr4spaabt4izq

Page 59 of Digest of Neurology and Psychiatry Vol. 43, Issue [page]

1975 Digest of Neurology and Psychiatry  
Fluidity of mood and emotion, impulsivity, instability, histrionic behavior, and even disturbances in motor, perceptual, and interpretive functions may emerge as components of the stress response.  ...  The feelings are not totally eliminated, however, and they may emerge in an exaggerated sense of “duty,” undue concern with detail, crippling indecisiveness, a fear of losing control, and even in attacks  ... 

Depressive Rumination and Co-Morbidity: Evidence for Brooding as a Transdiagnostic Process

Edward R. Watkins
2009 Journal of Rational-Emotive & Cognitive-Behavior Therapy  
disorder, and rumination was associated with traits associated with borderline personality disorder, most notably self-report of unstable relationships and inconsistent sense of self.  ...  As predicted, rumination was associated with reports of sexual abuse. Inconsistent with previous findings, there was no gender difference in rumination.  ...  Open Access This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided  ... 
doi:10.1007/s10942-009-0098-9 pmid:19718267 pmcid:PMC2731158 fatcat:2liambpgvjfm7jhmbwzxgtrfpe

The Phenomenology and Predictive Processing of Time in Depression [chapter]

Zachariah A. Neemeh, Shaun Gallagher
2020 The Philosophy and Science of Predictive Processing  
Z.A.N. would like to thank the Institute of Intelligent Systems for a travel grant to present an earlier version of this paper at the XXIV World Congress of Philosophy. Notes  ...  of flow), experiential affect, and mood, respectively.  ...  They refer to this instability metaphorically as a "distrust of the present. " The sense of flow arises as the system gives up one hypothesis and settles on a new one due to its propensity for distrusting  ... 
doi:10.5040/ fatcat:2i6axz3z5zc7lkzaogirnpm4ey

Development and Evaluation of a Smartphone-Based Measure of Social Rhythms for Bipolar Disorder

Mark Matthews, Saeed Abdullah, Elizabeth Murnane, Stephen Voida, Tanzeem Choudhury, Geri Gay, Ellen Frank
2016 Assessment (Odessa, Fla.)  
In this phase, the therapeutic goal for the patient is to understand the dynamic relationship between routine instabilities and mood fluctuations.  ...  An electronic version of the SRM could both help address the issue of self-report bias and also relieve some of the burden for patients of self-tracking by harnessing latent passive sensing capabilities  ... 
doi:10.1177/1073191116656794 pmid:27358214 fatcat:ndahvdxzivfqblwaeiqtcqpvce

Self-monitoring practices, attitudes, and needs of individuals with bipolar disorder: implications for the design of technologies to manage mental health

Elizabeth L Murnane, Dan Cosley, Pamara Chang, Shion Guha, Ellen Frank, Geri Gay, Mark Matthews
2016 JAMIA Journal of the American Medical Informatics Association  
13,40 and MONARCA 41 have attempted to utilize such sensing strategies to predict mood episodes and provide feedback to users.  ...  sense of emotional balance.  ...  ., and E.F. all have an equity interest in HealthRhythms (, a startup company developing apps for patients with bipolar disorder.  ... 
doi:10.1093/jamia/ocv165 pmid:26911822 fatcat:5a2n32ravjditeiidzfjjzmafu

Relationship between Personality Disorder Functioning Styles and the Emotional States in Bipolar I and II Disorders

Jiashu Yao, You Xu, Yanhua Qin, Jing Liu, Yuedi Shen, Wei Wang, Wei Chen, Marianna Mazza
2015 PLoS ONE  
In BD II, Borderline, Dependant, Paranoid (-) and Schizoid (-) predicted PVP; Borderline predicted MDQ; Passive-Aggressive and Schizoid (-) predicted HCL-32.  ...  Conclusion Besides confirming the different predictability of the 11 functioning styles of personality disorder to BD I and II, we found that the prediction was more common in BD II, which might underlie  ...  The Passive-Aggressive and Schizoid (-) styles predicted the HCL-32 scale.  ... 
doi:10.1371/journal.pone.0117353 pmid:25625553 pmcid:PMC4307975 fatcat:w2tvem35d5h73iym5yupf53xfe

The promise of digital mood tracking technologies: are we heading on the right track?

Gin S Malhi, Amber Hamilton, Grace Morris, Zola Mannie, Pritha Das, Tim Outhred
2017 Evidence-Based Mental Health  
The growing understanding that mood disorders are dynamic in nature and fluctuate over variable epochs of time has compelled researchers to develop innovative methods of monitoring mood.  ...  Traditionally, assessments of mood have been conducted by means of clinical interviews and paper surveys.  ...  be used to predict mood states.  ... 
doi:10.1136/eb-2017-102757 pmid:28855245 fatcat:lnz4uawutfeihdwgccafukcgba

Circadian Computing: Sensing, Modeling, and Maintaining Biological Rhythms [chapter]

Saeed Abdullah, Elizabeth L. Murnane, Mark Matthews, Tanzeem Choudhury
2017 Mobile Health  
We use a combination of automated sensing of behavioral traits along with manual ecological momentary assessments (EMA) to model body clock patterns, detect disruptions, and drive in-situ interventions  ...  Our biological processes vary significantly, predictably, and idiosyncratically throughout the day in accordance with these circadian rhythms, which in turn influence our physical and mental performance  ...  daily routines, predict mood episodes, and provide personalized feedback to users.  ... 
doi:10.1007/978-3-319-51394-2_3 fatcat:zorrlea2pjeafed3g2lf3riuy4

Critical Fluctuations as an Early-Warning Signal for Sudden Gains and Losses in Patients Receiving Psychotherapy for Mood Disorders

Merlijn Olthof, Fred Hasselman, Guido Strunk, Marieke van Rooij, Benjamin Aas, Marieke A. Helmich, Günter Schiepek, Anna Lichtwarck-Aschoff
2019 Clinical Psychological Science  
These results show that EWSs can be used for real-time prediction of sudden gains and losses in clinical practice.  ...  We tested whether EWSs in patients' daily self-ratings of the psychotherapeutic process predicted future sudden gains and losses.  ...  The result that sudden gains and losses can be predicted with EWSs is in line with previous research showing that instability and fluctuations in the therapeutic process are related to better treatment  ... 
doi:10.1177/2167702619865969 fatcat:36xugj2hc5h5liqtjztxeiugny

Quality of couples' relationship and adjustment to metastatic breast cancer

Janine Giese-Davis, Kaye Hermanson, Cheryl Koopman, David Weibel, David Spiegel
2000 Journal of family psychology  
Partner passive coping with a recent cancer event: Ways of Coping Scale(WOC).  ...  Summary of Simultaneous Regression Analysis for Variables Predicting Metastatic Breast Cancer Patients’ Mood Disturbance (POMS Score; n = 48) Variable Partner POMS Partner passive coping Patient Cohesion  ... 
doi:10.1037/0893-3200.14.2.251 fatcat:t2gtqbhwpvau5orghnavuuk77q
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