Time series models of symptoms in schizophrenia (original) (raw)
Related papers
Symptom trajectories in psychotic episodes
Comprehensive Psychiatry, 2002
Whereas the cross-sectional structure of schizophrenic symptoms has been studied extensively, little is known about the development of symptoms during acute episodes. In this study, symptom trajectories of 46 schizophrenia spectrum patients were examined based on daily observation during an average treatment period of 104 days. A novel time series approach was used to identify initial phases of response and other descriptive features of the trajectories. The results yielded five dynamical factors: (1) overall level of positive symptoms, (2) duration of nonspecific response, (3) slope of response in all symptom domains, (4) enduring negative symptoms, and (5) duration of response regarding psychoticity. Compared to patients with an acute schizophrenia-like psychotic disorder, schizophrenia and schizoaffective disorder patients ranked higher in factor 4 (enduring negative symptoms). They tended towards a lower level of positive symptoms and showed a less prominent response to treatment. The examination of a subsample of 19 patients with relapse indicated a prolonged duration of initial treatment response regarding psychoticity. The results support the validity of this approach for the description of symptom trajectories. Copyright 2002, Elsevier Science (USA). All rights reserved.
Dynamical analysis of schizophrenia courses
Biological Psychiatry, 1997
In order to assess the working hypothesis that schizophrenia may be viewed as a nonlinear dynamical disease, we examined the long-term psychotici~' dynamics of 14 patients'. The data consist of daily ratings of psychopathology observed for 200 or more consecutive days in each patient. We implemented nonlinear dynamical analysis methods with a potential of being applicable even to relatively short and noisy time series: two different forecasting approaches combined with surrogate methods that allow statistical testing in each single case. The resulting classification of dynamics gives evidence that eight patients show nonlinear evolutions of symptom courses. Four cases can be modeled linearly, two as random processes. Thus, a larger proportion of the schizophrenic psychoses we studied shows nonlinear time courses. In this way the validi~.' of the concept of dynamical diseases could be supported on statistical grounds in this important area of psychopathology. The nonlinear view--a low-dimensional nonlinear system generating psychotic symptoms--may provide the foundation for a more parsimonious theo©' of schizophrenia compared to traditional multicausal models. In several of the nonlinear cases we also observed the qualitative ".fingerprint" of deterministic chaos: a decay of deterministic features of the course of disorder with time.
Objective: This paper illustrates the process of constructing, selecting and applying simple measures in order to empirically derive patterns of course of psychotic episodes in schizophrenia. Method: Data were collected with a composite instrument constructed for a multi-centre, follow-up randomized controlled trial of adherence therapy for people with schizophrenia. The instrument included a retrospective weekly assessment of psychotic/non-psychotic status, which was used to derive the measures, and the DSM-IV course specifi ers. Results: The measures discriminated well between different course patterns and identifi ed homogeneous clusters of subjects which correlated with the groups derived from the DSM-IV course specifi ers. Conclusions: The new measures provide an empirical basis to identify specifi c patterns of course and to differentiate patients according to pre-defi ned criteria. They can be used in follow-up studies as measures of outcome, to investigate correlations between variables and to identify potential predictors of outcome.
Modelling Approaches: The Case of Schizophrenia
Pharmacoeconomics, 2008
interrupted by acute episodes (or relapses). The course of the disease may vary considerably between patients. Patient histories show considerable inter-and even intra-individual variability. We provide a critical assessment of the advantages and disadvantages of three modelling techniques that have been used in schizophrenia: decision trees, (cohort and micro-simulation) Markov models and discrete event simulation models. These modelling techniques are compared in terms of building time, data requirements, medico-scientific experience, simulation time, clinical representation, and their ability to deal with patient heterogeneity, the timing of events, prior events, patient interaction, interaction between covariates and variability (first-order uncertainty).
Modelling the treated course of schizophrenia: Development of a discrete event simulation model
PharmacoEconomics, 2005
In schizophrenia, modelling techniques may be needed to estimate the long-term costs and effects of new interventions. However, it seems that a simple direct link between symptoms and costs does not exist. Decisions about whether a patient will be hospitalized or admitted to a different healthcare setting are based not only on symptoms but also on social and environmental factors. This paper describes the development of a model to assess the dependencies between a broad range of parameters in the treatment of schizophrenia. In particular, the model attempts to incorporate social and environmental factors into the decision-making process for the prescription of new drugs to patients. The model was used to analyse the potential benefits of improving compliance with medication by 20% in patients in the UK. A discrete event simulation (DES) model was developed, to describe a cohort of schizophrenia patients with multiple psychotic episodes. The model takes into account the patient's sex, disease severity, potential risk of harm to self and society, and social and environmental factors. Other variables that change over time include the number of psychiatric consultations, the presence of psychotic episodes, symptoms, treatments, compliance, side-effects, the lack of ability to take care of him/herself, care setting and risk of harm. Outcomes are costs, psychotic episodes and symptoms. Univariate and multivariate sensitivity analyses were performed. Direct medical costs were considered (year of costing 2002), applying a 6.0% discount rate for costs and a 1.5% discount rate for outcome. The timeframe of the model is 5 years. When 50% of the decisions about the patient care setting are based on symptoms, a 20% increase in compliance was estimated to save £16 147 and to avoid 0.55 psychotic episodes per patient over 5 years. Sensitivity analysis showed that the costs savings associated with increased compliance are robust over a range of variations in parameters. DES offers a flexible structure for modelling a disease, taking into account how a patient's history affects the course of the disease over time. This approach is particularly pertinent to schizophrenia, in which treatment decisions are complex. The model shows that better compliance increases the time between relapses, decreases the symptom score, and reduces the requirement
Schizophrenia Research, 2000
Prodromal symptoms, including disturbances of perceptions, beliefs, cognition, affect, and behavior, are often the first symptoms of schizophrenia. Little is understood about the initial, prodromal stage of schizophrenia, despite the compelling research and clinical need. The development and psychometric properties of a new, time-efficient instrument to characterize and date the initial symptoms of a psychotic illnesses, the Symptom Onset in Schizophrenia (SOS) scale, is described in this paper. The SOS rates the presence and dates the onset of 16 general prodromal, positive, negative, and disorganizational symptoms, as well as a clinician, family, and patient global rating of onset of illness. Inter-rater reliability for the presence of each symptom in 35 patients with schizophrenia, schizoaffective, or schizophreniform disorder was good to excellent, with kappa coefficient >0.7 for 12 items, and >0.5 for all items. Agreement on symptom duration was good to excellent for individual items (ICC=0.7-1.0) and for global rating of duration of illness (ICC=0.97). Our data indicate that the SOS is a reliable, valid, time-efficient tool useful to retrospectively assess the onset of schizophrenia and related psychotic disorders. Further study is underway to evaluate other psychometric properties of the SOS, including test-retest reliability and predictive validity.
Capturing the Ebb and Flow of Psychiatric Symptoms With Dynamical Systems Models
American Journal of Psychiatry, 2009
Objective: Psychiatric symptoms play a crucial role in psychology and psychiatry. However, little is known about how dimensions of symptoms-other than symptom level-relate to psychiatric outcomes. Until recently, methods for measuring dynamic aspects of symptoms have not been available to clinicians or researchers. The authors sought to test whether systematic patterns of change in psychiatric symptoms can be recovered across weekly assessments of individuals at high risk for violence. A secondary objective was to explore whether dynamic features of symptoms (specifically, oscillation speed and dysregulation) are concurrently associated with violence, an important indicator of functional impairment for these individuals.
Symptom dimensions stability over time in recent onset psychosis: A prospective study
Schizophrenia Research, 2022
Background: The factorial structure of schizophrenia symptoms has been much debated but little is known on its degree of unicity, specificity as well as its dynamic over time. Symptom differentiation is a phenomenon according to which patients' symptoms could differentiate from one another during illness to form more independent, distinct dimensions. On the contrary, symptom dedifferentiation is an increase in the correlations between those symptoms over time. The goal of this study was to investigate symptom differentiation or dedifferentiation over time in recent onset psychosis using the Positive and Negative Syndrome Scale. Methods: A confirmatory factor analysis model based on the consensus five-factor model of the Positive and Negative Syndrome Scale for schizophrenia was estimated on seven different time points over a three-year period. A general factor capturing common variance between every symptom was also included. Explained common variance was computed for the general factor and each specific factor. Results: Three hundred and sixty-two recent onset psychosis patients were assessed. Results showed no evidence for either symptom differentiation or dedifferentiation over time. Specific symptoms accounted for >70 % of the variance suggesting a high degree of specificity of the symptomatology. Conclusions: Overall, this study adds support for a highly multidimensional approach to clinical symptom assessment with an explicit focus on depression. The premise behind the staging approach being inherently one-dimensional, implications for further research is discussed.
Statistical modeling of psychosis data
Computer Methods and Programs in Biomedicine, 2010
c o m p u t e r m e t h o d s a n d p r o g r a m s i n b i o m e d i c i n e 1 0 0 ( 2 0 1 0 ) 222-236 Psychosis Brief Psychiatric Rating Scale-F2 Plackett-Burman design Statistical modeling a b s t r a c t