Video-Based Analysis of Bodily Startle and Subsequent Emotional Facial Expression in Posttraumatic Stress Disorder

Anxiety, depression, and post-traumatic stress disorder in nurses exposed to horizontal violence: a network analysis

BACKGROUND

Horizontal violence can cause serious mental health problems for nurses, particularly anxiety, depression, and post-traumatic stress disorder. However, the intrinsic linkage mechanism between mental symptoms of anxiety, depression, and post-traumatic stress disorder in nurses exposed to horizontal violence is unclear. This study aims to elucidate the characteristics of anxiety, depression, and post-traumatic stress disorder networks among nurses with horizontal violence exposure.

METHODS

Data for this cross-sectional study were obtained from the baseline portion of a short longitudinal survey conducted at four tertiary hospitals in Shandong Province, China. A total of 510 nurses with horizontal violence exposure completed the General Information Scale, the Negative Acts Questionnaire, the Seven-item Generalized Anxiety Disorder Scale, the Nine-item Patient Health Questionnaire, and the Four-item SPAN. The network model was constructed using network analysis. The expected influence and the bridge expected influence of nodes were calculated. The stability and accuracy of the network were estimated.

RESULTS

The results show that A4 (Trouble relaxing) and P1 (Startle) had the highest expected influence in the network. D9 (Suicidality ideation) and A5 (Restlessness) were the key bridge symptoms.

CONCLUSIONS

"Trouble relaxing", "Startle", "Suicidality ideation", and "Restlessness" are all mental symptoms that need to be urgently improved the most in nurses exposed to horizontal violence. Nursing administrators and policymakers should implement mental health intervention programs for these symptoms as early as possible to maximize nurses' mental health.

Digital Phenotyping for Differential Diagnosis of Major Depressive Episode: Narrative Review

BACKGROUND

Major depressive episode (MDE) is a common clinical syndrome. It can be found in different pathologies such as major depressive disorder (MDD), bipolar disorder (BD), posttraumatic stress disorder (PTSD), or even occur in the context of psychological trauma. However, only 1 syndrome is described in international classifications (Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition [DSM-5]/International Classification of Diseases 11th Revision [ICD-11]), which do not take into account the underlying pathology at the origin of the MDE. Clinical interviews are currently the best source of information to obtain the etiological diagnosis of MDE. Nevertheless, it does not allow an early diagnosis and there are no objective measures of extracted clinical information. To remedy this, the use of digital tools and their correlation with clinical symptomatology could be useful.

OBJECTIVE

We aimed to review the current application of digital tools for MDE diagnosis while highlighting shortcomings for further research. In addition, our work was focused on digital devices easy to use during clinical interview and mental health issues where depression is common.

METHODS

We conducted a narrative review of the use of digital tools during clinical interviews for MDE by searching papers published in PubMed/MEDLINE, Web of Science, and Google Scholar databases since February 2010. The search was conducted from June to September 2021. Potentially relevant papers were then compared against a checklist for relevance and reviewed independently for inclusion, with focus on 4 allocated topics of (1) automated voice analysis, behavior analysis by (2) video and physiological measures, (3) heart rate variability (HRV), and (4) electrodermal activity (EDA). For this purpose, we were interested in 4 frequently found clinical conditions in which MDE can occur: (1) MDD, (2) BD, (3) PTSD, and (4) psychological trauma.

RESULTS

A total of 74 relevant papers on the subject were qualitatively analyzed and the information was synthesized. Thus, a digital phenotype of MDE seems to emerge consisting of modifications in speech features (namely, temporal, prosodic, spectral, source, and formants) and in speech content, modifications in nonverbal behavior (head, hand, body and eyes movement, facial expressivity, and gaze), and a decrease in physiological measurements (HRV and EDA). We not only found similarities but also differences when MDE occurs in MDD, BD, PTSD, or psychological trauma. However, comparative studies were rare in BD or PTSD conditions, which does not allow us to identify clear and distinct digital phenotypes.

CONCLUSIONS

Our search identified markers from several modalities that hold promise for helping with a more objective diagnosis of MDE. To validate their potential, further longitudinal and prospective studies are needed.

Is PTSD an Evolutionary Survival Adaptation Initiated by Unrestrained Cytokine Signaling and Maintained by Epigenetic Change?

INTRODUCTION

Treatment outcomes for PTSD with current psychological therapies are poor, with very few patients achieving sustained symptom remission. A number of authors have identified physiological and immune disturbances in Post Traumatic Stress Disorder (PTSD) patients, but there is no unifying hypothesis that explains the myriad features of the disorder.

MATERIALS AND METHODS

The medical literature was reviewed over a 6-year period primarily using the medical database PUBMED.

RESULTS

The literature contains numerous papers that have identified a range of physiological and immune dysfunction in association with PTSD. This paper proposes that unrestrained cytokine signaling induces epigenetic changes that promote an evolutionary survival adaptation, which maintains a defensive PTSD phenotype. The brain can associate immune signaling with past threat and initiate a defensive behavioral response. The sympathetic nervous system is pro-inflammatory, while the parasympathetic nervous system is anti-inflammatory. Prolonged cholinergic withdrawal will promote a chronic inflammatory state. The innate immune cytokine IL-1β has pleiotropic properties and can regulate autonomic, glucocorticoid, and glutamate receptor functions, sleep, memory, and epigenetic enzymes. Changes in epigenetic enzyme activity can potentially alter phenotype and induce an adaptation. Levels of IL-1β correlate with severity and duration of PTSD and PTSD can be prevented by bolus administration of hydrocortisone in acute sepsis, consistent with unrestrained inflammation being a risk factor for PTSD. The nervous and immune systems engage in crosstalk, governed by common receptors. The benefits of currently used psychiatric medication may arise from immune, as well as synaptic, modulation. The psychedelic drugs (3,4-Methylenedioxymethamphetamine (MDMA), psilocybin, and ketamine) have potent immunosuppressive and anti-inflammatory effects on the adaptive immune system, which may contribute to their reported benefit in PTSD. There may be distinct PTSD phenotypes induced by innate and adaptive cytokine signaling.

CONCLUSION

In order for an organism to survive, it must adapt to its environment. Cytokines signal danger to the brain and can induce epigenetic changes that result in a persistent defensive phenotype. PTSD may be the price individuals pay for the genomic flexibility that promotes adaptation and survival.

Deep learning-based classification of posttraumatic stress disorder and depression following trauma utilizing visual and auditory markers of arousal and mood

BACKGROUND

Visual and auditory signs of patient functioning have long been used for clinical diagnosis, treatment selection, and prognosis. Direct measurement and quantification of these signals can aim to improve the consistency, sensitivity, and scalability of clinical assessment. Currently, we investigate if machine learning-based computer vision (CV), semantic, and acoustic analysis can capture clinical features from free speech responses to a brief interview 1 month post-trauma that accurately classify major depressive disorder (MDD) and posttraumatic stress disorder (PTSD).

METHODS

N = 81 patients admitted to an emergency department (ED) of a Level-1 Trauma Unit following a life-threatening traumatic event participated in an open-ended qualitative interview with a para-professional about their experience 1 month following admission. A deep neural network was utilized to extract facial features of emotion and their intensity, movement parameters, speech prosody, and natural language content. These features were utilized as inputs to classify PTSD and MDD cross-sectionally.

RESULTS

Both video- and audio-based markers contributed to good discriminatory classification accuracy. The algorithm discriminates PTSD status at 1 month after ED admission with an AUC of 0.90 (weighted average precision = 0.83, recall = 0.84, and f1-score = 0.83) as well as depression status at 1 month after ED admission with an AUC of 0.86 (weighted average precision = 0.83, recall = 0.82, and f1-score = 0.82).

CONCLUSIONS

Direct clinical observation during post-trauma free speech using deep learning identifies digital markers that can be utilized to classify MDD and PTSD status.

The neural correlates of trauma-related autobiographical memory in posttraumatic stress disorder: A meta-analysis

BACKGROUND

Autobiographical memory (AM) refers to memories of events that are personally relevant and are remembered from one's own past. The AM network is a distributed brain network comprised largely by prefrontal medial and posteromedial cortical brain regions, which together facilitate AM. Autobiographical memories with high arousal and negatively valenced emotional states are thought to be retrieved more readily and re-experienced more vividly. This is critical in the case of trauma-related AMs, which are related to altered phenomenological experiences as well as aberrations to the underlying neural systems in posttraumatic stress disorder (PTSD). Critically, these alterations to the AM network have not been explored recently and have never been analyzed with consideration to the different processes of AM, them being retrieval and re-experiencing.

METHODS

We conducted a series of effect-size signed differential mapping meta-analyses across twenty-eight studies investigating the neural correlates of trauma-related AMs in participants with PTSD as compared with controls. Studies included either trauma-related scripts or trauma-related materials (i.e., sounds, images, pictures) implemented to evoke the recollection of a trauma-related memory.

RESULTS

The meta-analyses revealed that control and PTSD participants displayed greater common brain activation of prefrontal medial and posteromedial cortices, respectively. Whereby the prefrontal medial cortices are suggested to facilitate retrieval monitoring, the posteromedial cortices are thought to enable the visual imagery processes of AM.

CONCLUSIONS

Taken together, reduced common activation of prefrontal cortices may be interpreted as a bias toward greater re-experiencing, where the more salient elements of the traumatic memory are relived as opposed to retrieved in a controlled manner in PTSD.

Multimodal analysis of startle type responses

BACKGROUND AND OBJECTIVE

This article presents a multimodal analysis of startle type responses using a variety of physiological, facial, and speech features. These multimodal components of the startle type response reflect complex brain-body reactions to a sudden and intense stimulus. Additionally, the proposed multimodal evaluation of reflexive and emotional reactions associated with the startle eliciting stimuli and underlying neural networks and pathways could be applied in diagnostics of different psychiatric and neurological diseases. Different startle type stimuli can be compared in the strength of their elicitation of startle responses, i.e. their potential to activate stress-related neural pathways, underlying biomarkers and corresponding behavioral reactions.

METHODS

An innovative method for measuring startle type responses using multimodal stimuli and multimodal feature analysis has been introduced. Individual's multimodal reflexive and emotional expressions during startle type elicitation have been assessed by corresponding physiological, speech and facial features on ten female students of psychology. Different startle eliciting stimuli like noise and airblast probes, as well as a variety of visual and auditory stimuli of different valence and arousal levels, based on International Affective Picture System (IAPS) images and/or sounds from International Affective Digitized Sounds (IADS) database, have been designed and tested. Combined together into more complex startle type stimuli, such composite stimuli can potentiate the evoked response of underlying neural networks, and corresponding neurotransmitters and neuromodulators as well; this is referred to as increased power of response elicitation. The intensity and magnitude of multimodal responses to selected startle type stimuli have been analyzed using effect sizes and medians of dominant multimodal features, i.e. skin conductance, eye blink, head movement, speech fundamental frequency and energy. The significance of the observed effects and comparisons between paradigms were evaluated using one-tailed t-tests and ANOVA methods, respectively. Skin conductance response habituation was analyzed using ANOVA and post hoc multiple comparison tests with the Dunn-Šidák correction.

RESULTS

The results revealed specific physiological, facial and vocal reflexive and emotional responses on selected five stimuli paradigms which included: (1) acoustic startle probes, (2) airblasts, (3) IAPS images, (4) IADS sounds, and (5) image-sound-airblast composite stimuli. Overall, composite and airblast paradigms resulted in the largest responses across all analyzed features, followed by sound and acoustic startle paradigms, while paradigm using images consistently elicited the smallest responses. In this context, power of response elicitation of the selected stimuli paradigms can be described according to the aggregated magnitude of the participants' multimodal responses. We also observed a habituation effect only in skin conductance response to acoustic startle, airblast and sound paradigms.

CONCLUSIONS

This study developed a system for paradigm design and stimuli generation, as well as real-time multimodal signal processing and feature calculation. Experimental paradigms for monitoring individual responses to stressful startle type stimuli were designed in order to compare the response elicitation power across various stimuli. The developed system, applied paradigms and obtained results might be useful in further research for evaluation of individuals' multimodal responses when they are faced with a variety of aversive emotional distractors and stressful situations.