Negative Symptoms and Avoidance of Social Interaction: A Study of Non-Verbal Behaviour

Worswick, Elizabeth; Dimic, Sara; Wildgrube, Christiane; Priebe, Stefan

doi:10.1159/000484414

Cited by 18 publications

(12 citation statements)

References 43 publications

(66 reference statements)

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“…They also manifest a reduced ability to express and maintain positive emotions [23, 24]. Finally, they tend to avoid interpersonal interactions and anticipate a lower amount of pleasure in such interactions [25, 26]. …”

Section: Introductionmentioning

confidence: 99%

Improving Pleasure and Motivation in Schizophrenia: A Randomized Controlled Clinical Trial

Favrod

Nguyen

Chaix

et al. 2019

Psychother Psychosom

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Background: Negative symptoms are frequent in patients with schizophrenia and are associated with marked impairments in social functioning. The efficacy of drug-based treatments and psychological interventions on primary negative symptoms remains limited. The Positive Emotions Programme for Schizophrenia (PEPS) is designed to improve pleasure and motivation in schizophrenia patients by targeting emotion regulation and cognitive skills relevant to apathy and anhedonia. The main hypothesis of this study is that patients who attend 8 one-hour sessions of PEPS and treatment as usual (TAU) will have lower total apathy-avolition and anhedonia-asociality composite scores on the Scale for the Assessment of Negative Symptoms (SANS) than patients who attend only TAU. Methods: Eighty participants diagnosed with schizophrenia or schizoaffective disorder were randomized to receive either TAU or PEPS + TAU. The participants were assessed by independent evaluators before randomization (T0), in a post-test after 8 weeks of treatment (T1) and at a 6-month follow-up (T2). Results: The post-test results and 6-month follow-up assessments according to an intention-to-treat analysis showed that the apathy and anhedonia composite scores on the SANS indicated statistically greater clinical improvements in PEPS participants than in non-PEPS participants. In the post-test, anhedonia but not apathy was significantly improved, thus favouring the PEPS condition. These results were sustained at the 6-month follow-up. Conclusions: PEPS is an effective intervention to reduce anhedonia in schizophrenia. PEPS is a short, easy-to-use, group-based, freely available intervention that is easy to implement in a variety of environments (ClinicalTrials.gov ID: NCT02593058).

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Section: Introductionmentioning

confidence: 99%

Improving Pleasure and Motivation in Schizophrenia: A Randomized Controlled Clinical Trial

Favrod

Nguyen

Chaix

et al. 2019

Psychother Psychosom

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“…In psychiatry, a lot of research focused on studying the nonverbal behaviour of patients with schizophrenia [12,13]. In these works, the non-verbal behaviour was manually annotated by human raters.…”

Section: Related Workmentioning

confidence: 99%

Can Automatic Facial Expression Analysis Be Used for Treatment Outcome Estimation in Schizophrenia?

Bishay

Priebe

Patras

2019

ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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Negative symptoms of schizophrenia include expressive deficits that are marked by a reduction in patients' behaviour. Analysing automatically non-verbal behaviour and exploiting the results for estimating symptom severity has drawn attention recently. However, those approaches are not accurate enough to be used for monitoring the changes in patient's symptom level during treatment interventions (i.e. the treatment outcome). In this paper, we propose a method that directly addresses the problem of Treatment Outcome Estimation (TOE) in schizophrenia-more specifically, is aimed at determining whether specific symptoms have improved or not by analysing jointly two videos of the same patient, one before and one after the treatment. The proposed architecture builds on Recurrent Neural Networks (RNNs) that learn differences in the patient behaviour before and after treatment. We validate the method in videotaped interviews for symptom assessment for 74 patients. Experimental results show that the proposed architecture achieves promising results for TOE in two different symptom assessment scales.

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“…Patients can also show impairment in the non-verbal behaviour that invites social interaction during clinical and nonclinical interviews [7]. Non-verbal behaviour was found to change during interviews according to symptom severity [8], [9], [10]. For instance, patients with high symptom severity tend to avoid interaction by nodding less, smiling less, and looking less at the interviewer [8].…”

Section: Introductionmentioning

confidence: 99%

SchiNet: Automatic Estimation of Symptoms of Schizophrenia from Facial Behaviour Analysis

Bishay

Palasek²,

Priebe

et al. 2021

IEEE Trans. Affective Comput.

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Patients with schizophrenia often display impairments in the expression of emotion and speech and those are observed in their facial behaviour. Automatic analysis of patients' facial expressions that is aimed at estimating symptoms of schizophrenia has received attention recently. However, the datasets that are typically used for training and evaluating the developed methods, contain only a small number of patients (4-34) and are recorded while the subjects were performing controlled tasks such as listening to life vignettes, or answering emotional questions. In this paper, we use videos of professional-patient interviews, in which symptoms were assessed in a standardised way as they should/may be assessed in practice, and which were recorded in realistic conditions (i.e. varying illumination levels and camera viewpoints) at the patients' homes or at mental health services. We automatically analyse the facial behaviour of 91 out-patients -this is almost 3 times the number of patients in other studies -and propose SchiNet, a novel neural network architecture that estimates expression-related symptoms in two different assessment interviews. We evaluate the proposed SchiNet for patient-independent prediction of symptoms of schizophrenia. Experimental results show that some automatically detected facial expressions are significantly correlated to symptoms of schizophrenia, and that the proposed network for estimating symptom severity delivers promising results.

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Negative Symptoms and Avoidance of Social Interaction: A Study of Non-Verbal Behaviour

Cited by 18 publications

References 43 publications

Improving Pleasure and Motivation in Schizophrenia: A Randomized Controlled Clinical Trial

Improving Pleasure and Motivation in Schizophrenia: A Randomized Controlled Clinical Trial

Can Automatic Facial Expression Analysis Be Used for Treatment Outcome Estimation in Schizophrenia?

SchiNet: Automatic Estimation of Symptoms of Schizophrenia from Facial Behaviour Analysis

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