[IDEM-depression: Characteristics and evaluation of an open group that combines psychoeducation and cognitive-behavior therapy]. / IDEM-dépression : caractéristiques et évaluation d'un groupe ouvert combinant psycho-éducation et thérapie cognitivo-comportementale.

INTRODUCTION: Depression is a highly prevalent mental illness that is associated with high rates of morbidity and functional impairment. At the psychiatric unit of the University Hospital of Strasbourg, France, we have developed an open group that combines psychoeducation and cognitive-behavior therapy (CBT), the information, discovery, exchange and mobilization for depression group (IDEM-depression). IDEM-depression is composed of 17 thematic, structured, and independent sessions, which address different aspects of depression (i.e., rumination, pharmacological treatments). Because of its flexible format, patients with varying degrees of depression severity (from remission up to severe depressive symptoms) and whose depression might be bipolar or unipolar, are able to participate in the group. Thus, the group is well suited to a large number of patients with major depression. In the present study we aimed at describing the IDEM-depression group and presenting results regarding patients' overall satisfaction, assessed via two self-report questionnaires (the Client Satisfaction Questionnaire, the CSQ-8, and the IDEM ad hoc questionnaire), as well as its effect on mood following each session assessed via a visual analog scale (VAS) ranging from 0 up to 100. METHOD: Sixty-five patients participated in 50 sessions of the IDEM-depression group in two hospitals in Alsace. 61% of the patients had bipolar disorder, and 41% of them were inpatients. Sessions took place on a weekly basis, lasted 2hours and were proposed by a CBT-trained clinical psychologist. Patients were asked to fill-out the VAS at the beginning and at the end of each session. Moreover, they were asked to fill-out the CSQ-8 and the IDEM ad hoc questionnaire when they left the group. Other than one session ("yoga and mindfulness"), all the sessions (16 out of 17) were structured on a Powerpoint© presentation. During the first hour information was given regarding the topic (i.e., rumination), and a shared CBT conceptualization of the topic was formulated by the participants and the psychologist. For most sessions, the first hour was therefore communication and information-based, whereas during the second hour participants were asked to participate in in-session behavioral experiments and/or to evaluate specific aspects of their behavior (thoughts, emotions, activity, mindful behavior) during the last few days. The therapist manual and the slides for each session are available via e-mail to the first author. RESULTS: Regarding the results, self-reported mood on the VAS was compared between the onset (225 VAS) and the end (225 VAS) of each session. Overall, results suggest that self-reported mood is significantly improved following the participation in sessions (t=-5. 87, P<0.001). Moreover, mean results on the CSQ-8 suggest that patients are highly satisfied with the group (M=24.46, SD=6.42). Among them, 82% reported a moderate-high satisfaction with the group. On the IDEM ad hoc questionnaire, patients reported an overall high satisfaction level regarding (i) the content of sessions, (ii) the duration of sessions, (iii) the frequency of sessions, (iv) how much they felt they could express themselves during sessions. In the qualitative comments of this questionnaire, patients reported that the group helped them to gain an understanding of the mechanisms involved in depression; to feel less isolated and guilty; and to learn about specific psychotherapeutic tools (i.e., mindfulness) and to try to implement them. CONCLUSION: Our results suggest that an IDEM-depression group is well suited to a wide-array of clinical pictures associated with depression (varying severity, bipolar or unipolar, inpatients and outpatients). This is probably due to its open-group format which is particularly well-adapted to the dynamic symptomatology associated with major depression, and may stimulate decentering in patients who have different levels of severity of symptoms but participate in the same session. Moreover, its impact on mood improvement, and the high satisfaction level reported by patients, seem to be related to its CBT and psychoeducation-based content on the one hand, which has shown its efficacy in depression. On the other hand, IDEM's structured open-group format might have also contributed to the improvement in mood and the overall good satisfaction reported by patients, through the social support provided by the group, improved feeling of self-efficiency, and its effect on stigmatization. Thus, IDEM-depression group is an efficacious, flexible, low-cost, and easy to implement (in different clinical settings) psychotherapeutic option for major depression.

Multigate doppler signal analysis using 3-D regularized long AR modelling.

Autoregressive (AR) modelling has already been proposed as an alternative to fast Fourier transform to process ultrasound (US) Doppler signals. Previous works introduced long AR models, set up under a regularization framework. The latter may be in 1-D (frequency) or 2-D (frequency and space or time). This study generalizes the spectrum regularization in the three dimensions frequency, space and time. The problem of the penalization function is addressed, and a new convex solution is proposed, taking into account possible nonstationarity of the Doppler signal. The parameter tuning is based on simulations using a standard Doppler signal model. The first results show that this processing improves the spectral estimation, and is well suited to flow interpretation.

Automatic sleep EEG analysis using filter banks.

Filter banks analysis is an easy and quick computing way to implement time-scale methods, these being well suited for short events as well as for large waveforms detection tasks. We propose a non-uniform oversampled filter banks to analyze sleep EEG single channel signal, the different subbands matching the classical EEG rhythms. In order to preserve the temporal shapes information, filter banks are oversampled. Coupling the informations conveyed by the different outputs allow to perform an automatic hypnogram.

EEG analysis using non-uniform oversampled filter banks.

Time-frequency or time-scale methods are well suited for short events as well as for large waveforms detection tasks. Filter banks analysis is an easy and quick computing way to implement these methods. We propose a non-uniform oversampled filter banks to analyze EEG single channel signal, the different subbands matching the classical EEG rhythms. We use oversampled filter banks to preserve the temporal shapes information. In order to illustrate this method, we show different spindle temporal structures as also their meaning in terms of sleep stage detection.