Markov Chain Model to Explain the Dynamics of Human Depression (original) (raw)
An Agent Model of Temporal Dynamics in Relapse and Recurrence in Depression
Lecture Notes in Computer Science, 2009
This paper presents a dynamic agent model of recurrences of a depression for an individual. Based on several personal characteristics and a representation of events (i.e. life events or daily hassles) the agent model can simulate whether a human agent that recovered from a depression will fall into a relapse or recurrence. A number of well-known relations between events and the course of depression are summarized from the literature and it is shown that the model exhibits those patterns. In addition, the agent model has been mathematically analyzed to find out which stable situations exist. Finally, it is pointed out how this model can be used in depression therapy, supported by a software agent.
Population health metrics, 2005
Most epidemiological studies of major depression report period prevalence estimates. These are of limited utility in characterizing the longitudinal epidemiology of this condition. Markov models provide a methodological framework for increasing the utility of epidemiological data. Markov models relating incidence and recovery to major depression prevalence have been described in a series of prior papers. In this paper, the models are extended to describe the longitudinal course of the disorder. Data from three national surveys conducted by the Canadian national statistical agency (Statistics Canada) were used in this analysis. These data were integrated using a Markov model. Incidence, recurrence and recovery were represented as weekly transition probabilities. Model parameters were calibrated to the survey estimates. The population was divided into three categories: low, moderate and high recurrence groups. The size of each category was approximated using lifetime data from a study...
Markov chain model and its application
Computers and Biomedical Research, 1986
This paper examines the use of the Markov chain model to study the condition of asthma patients with respect to seasonal variations. The model can be utilized for predicting the health status of these patients. 0 1986 Academic PESS. ITIC.
Depression as a dynamical disease
Biological Psychiatry, 1996
Mathematical models are helpful in the understanding of diseases through the use of dynamical indicators. A previous study has shown that brain activity can be characterized by a decrease of dynamical complexity in depressive subjects. The present paper confirms and extends these conclusions through the use of recent methodological advances: first episode and recurrent patients strongly differ in their dynamical response to therapeutic interventions. These results emphasize the need for clinical follow-ups to avoid recurrence and the necessity of specific therapeutic intervention in the case of recurrent patients.
Temporal course of change of depression
Journal of Consulting and Clinical Psychology, 1993
Two hundred fifty moderately to severely depressed outpatients were randomly assigned to 16 weeks of cognitive-behavioral therapy, interpersonal psychotherapy, imipramine plus clinical management (IMI-CM), or pill placebo plus clinical management. Two hundred thirty-nine patients actually began treatment. The most rapid change in depressive symptoms occurred in the IMI-CM condition, which achieved significantly better results than the other treatments at 8 and 12 weeks on 1 or more variables. Change over the course of treatment on variables hypothesized to be most specifically affected by the respective treatments was found only in the case of pharmacotherapy, in which imipramine produced significantly greater changes on the endogenous measure at 8 and 12 weeks. The temporal course of change of depressive symptoms for patients receiving different types of treatment is of interest from a clinical perspective and may help us better to understand the nature of depression, the nature of the treatments, and their
2016
Depression is a complex illness that involves the instability of biological and psychological structures in an individual. These disturbances make a depressed person to be affected in the personal relationships within his social circles and to be unable to fulfill normal daily activities as expected. Once depressed individuals recognize the need for help, they might be part of ‘therapeutic essays’ based on doctors´ experience and contemporary advances. These trial and error treatments can lead to unintended consequences that could worsen depression symptoms. Therefore, personalized treatments (a currently buzz term in the medical domain) are needed to reduce the time that an individual remains in a depressed condition. This paper contributes to treatment personalization of depression by presenting the first comprehensive feedback oriented model of the cognitive and biological structures involved in depression and how different treatments may bring the main affected indicators during...
Treatment and Prevention of Depression
Psychological Science in the Public Interest, 2002
Depression is one of the most common and debilitating psychiatric disorders and is a leading cause of suicide. Most people who become depressed will have multiple episodes, and some depressions are chronic. Persons with bipolar disorder will also have manic or hypomanic episodes. Given the recurrent nature of the disorder, it is important not just to treat the acute episode, but also to protect against its return and the onset of subsequent episodes. Several types of interventions have been shown to be efficacious in treating depression. The antidepressant medications are relatively safe and work for many patients, but there is no evidence that they reduce risk of recurrence once their use is terminated. The different medication classes are roughly comparable in efficacy, although some are easier to tolerate than are others. About half of all patients will respond to a given medication, and many of those who do not will respond to some other agent or to a combination of medications....
Away from a unitary model of depression
Behavior Therapy, 1980
Traditional psychiatric and current behavioral models have presented depression as a unitary phenomenon with one primary cause This paper posits that it is more conceptually and climcally useful to view depression as a label for a complex pattern of responses with a multiplicity of causes. When a chent's presenting probem is "depression," each of the problem areas characteristic of depression should be assessed, and the treatment procedure(s) should be matched to the problem area(s) 122
Static versus dynamic structural models of depression: The case of the CES-D
2002
La dépression comprend différentes facettes dont des symptômes interpersonnels, cognitifs, affectifs et somatiques. En effet, la majorité des mesures de la dépression sont de nature multidimensionnelle. Néanmoins, les utilisateurs de ces mesures utilisent typiquement le score total ou composé plutôt que le score individuel des dimensions. Nous proposons un examen plus en profondeur de la nature des relations entre ces dimensions sous-jacentes qui peut aider notre compréhension de la dépression. Des analyses par équations structurelles ont été utilisées auprès de 1,734 sujets afin de vérifier les relations de types statique (structures factorielles) et dynamique (modélisation causale) entre les dimensions de la version française du CES-D (Radloff, 1977). Les résultats des analyses transversales et prospectives soutiennent des liens de type causal entre les symptômes de la dépression. Ces résultats sont comparés à ceux des analyses factorielles hiérarchiques. Depression is composed of multiple subcomponents including social, cognitive, affective, and somatic symptomatology. Many widely used self-report scales are also multidimensional, suggesting that the subcomponents of depression are empirically differentiated, yet the use of a composite score is the common practice. The authors argue that a closer examination of the subscales of symptom inventories, and their interrelationships, can further our understanding of the development and persistence of depression. Structural equation modeling is used on the French version of CES-D responses (Radloff, 1977) from 1,734 participants, providing an explicit test of causal relations between several response classes commonly associated with depression. These structural models are consistent with a view of depression as a process that unfolds over time and are tested within both a cross-sectional and a prospective framework. They are compared to a higher-order factor model which speaks to the nature, but not the development, of depression. Mots-clés : Dépression, concept multidimensionnel, version française du CES-D, analyses factorielles confirmatoires, analyses par équations structurelles, relations statiques versus dynamiques