RESUMO
BACKGROUND: The detection of early warning signs is essential in the long-term treatment of bipolar disorders. However, in bipolar patients' daily life and outpatient treatment the assessment of upcoming state changes faces several difficulties. In this trial, we examine the effectiveness of a smartphone based automated feedback about ambulatory assessed early warning signs in prolonging states of euthymia and therefore preventing hospitalization. This study aims to assess, whether patients experience longer episodes of euthymia, when their treating psychiatrists receive automated feedback about changes in communication and activity. With this additional information an intervention at an earlier stage in the development of mania or depression could be facilitated. We expect that the amount of time will be longer between affective episodes in the intervention group. METHODS/DESIGN: The current study is designed as a randomized, multi-center, observer-blind, active-control, parallel group trial within a nationwide research project on the topic of innovative methods for diagnostics, prevention and interventions of bipolar disorders. One hundred and twenty patients with bipolar disorder will be randomly assigned to (1) the experimental group with included automated feedback or (2) the control group without feedback. During the intervention phase, the psychopathologic state of all participants is assessed every four weeks over 18 months. Kaplan-Meier estimators will be used for estimating the survival functions, a Log-Rank test will be used to formally compare time to a new episode across treatment groups. An intention-to-treat analysis will include data from all randomized patients. DISCUSSION: This article describes the design of a clinical trial investigating the effectiveness of a smartphone-based feedback loop. This feedback loop is meant to elicit early interventions at the detection of warning signs for the prevention of affective episodes in bipolar patients. This approach will hopefully improve the chances of a timely intervention helping patients to keep a balanced mood for longer periods of time. In detail, if our hypothesis can be confirmed, clinical practice treating psychiatrists will be enabled to react quickly when changes are automatically detected. Therefore, outpatients would receive an even more individually tailored treatment concerning time and frequency of doctor's appointments. TRIAL REGISTRATION: ClinicalTrials.gov : NCT02782910 : Title: "Smartphone-based Ambulatory Assessment of Early Warning Signs (BipoLife_A3)". Registered May 25 2016. Protocol Amendment Number: 03. Issue Date: 26 March 2018. Author(s): ES.
Assuntos
Assistência Ambulatorial/métodos , Transtorno Bipolar/diagnóstico , Testes Psicológicos , Smartphone , Telemedicina/métodos , Adulto , Afeto , Transtorno Bipolar/psicologia , Depressão/diagnóstico , Depressão/psicologia , Feminino , Humanos , Assistência de Longa Duração , Masculino , Pacientes Ambulatoriais/psicologia , Valor Preditivo dos Testes , Ensaios Clínicos Controlados Aleatórios como Assunto , Reprodutibilidade dos Testes , Método Simples-Cego , Fatores de TempoRESUMO
BACKGROUND: Digital phenotyping promises to unobtrusively obtaining a continuous and objective input of symptomatology from patients' daily lives. The prime example are bipolar disorders, as smartphone parameters directly reflect bipolar symptomatology. Empirical studies, however, have yielded inconsistent findings. We believe that three main shortcomings have to be addressed to fully leverage the potential of digital phenotyping: short assessment periods, rare outcome assessments, and an extreme fragmentation of parameters without an integrative analytical strategy. METHODS: To demonstrate how to overcome these shortcomings, we conducted frequent (biweekly) dimensional and categorical expert ratings and daily self-ratings over an extensive assessment period (12 months) in 29 patients with bipolar disorder. Digital phenotypes were monitored continuously. As an integrative analytical strategy, we used structural equation modelling to build latent psychopathological outcomes (mania, depression) and latent digital phenotype predictors (sleep, activity, communicativeness). OUTCOMES: Combining gold-standard categorical expert ratings with dimensional self and expert ratings resulted in two latent outcomes (mania and depression) with statistically meaningful factor loadings that dynamically varied over 299 days. Latent digital phenotypes of sleep and activity were associated with same-day latent manic psychopathology, suggesting that psychopathological alterations in bipolar disorders relate to domains (latent variables of sleep and activity) and not only to specific behaviors (such as the number of declined incoming calls). The identification of latent psychopathological outcomes that dimensionally vary on a daily basis will enable to empirically determine which combination of digital phenotypes at which days prior to an upcoming episode are viable as digital prodromal predictors.
RESUMO
Diagnostic assessments for dementia include the evaluation of subjective memory impairment, dementia worries, or depressive symptoms. Data on the predictive value of these factors remain unclear, and varying help-seeking behavior may contribute to this finding. We investigate whether differentiating help-seeking motivation from other psychological factors associated with cognitive impairment would enhance the prediction of diagnostic outcomes in a memory clinic. We obtained information on help-seeking motivation from 171 patients who underwent routine diagnostic assessments. Utilizing a discriminant correspondence analysis, our results indicate that extrinsic motivation increases the likelihood of receiving a dementia diagnosis, whereas depression or the duration of deficits carries discriminatory information to further guide the differentiation of prodromal dementia. Recognizing motivational aspects of help-seeking behavior can complement the clinical evaluation of cognitive performance.