The differential impact of holocaust trauma across three generations

In the current thesis, the reasons for the differential impact of Holocaust trauma on Holocaust survivors, and the differential intergenerational transmission of this trauma to survivors’ children and grandchildren were explored. A model specifically related to Holocaust trauma and its transmission was developed based on trauma, family systems and attachment theories as well as theoretical and anecdotal conjecture in the Holocaust literature. The Model of the Differential Impact of Holocaust Trauma across Three Generations was tested firstly by extensive meta-analyses of the literature pertaining to the psychological health of Holocaust survivors and their descendants and secondly via analysis of empirical study data. The meta-analyses reported in this thesis represent the first conducted with research pertaining to Holocaust survivors and grandchildren of Holocaust survivors. The meta-analysis of research conducted with children of survivors is the first to include both published and unpublished research. Meta-analytic techniques such as meta-regression and sub-set meta-analyses provided new information regarding the influence of a number of unmeasured demographic variables on the psychological health of Holocaust survivors and descendants. Based on the results of the meta-analyses it was concluded that Holocaust survivors and their children and grandchildren suffer from a statistically significantly higher level or greater severity of psychological symptoms than the general population. However it was also concluded that there is statistically significant variation in psychological health within the Holocaust survivor and descendant populations. Demographic variables which may explain a substantial amount of this variation have been largely under-assessed in the literature and so an empirical study was needed to clarify the role of demographics in determining survivor and descendant mental health. A total of 124 participants took part in the empirical study conducted for this thesis with 27 Holocaust survivors, 69 children of survivors and 28 grandchildren of survivors. A worldwide recruitment process was used to obtain these participants. Among the demographic variables assessed in the empirical study, aspects of the survivors’ Holocaust trauma (namely the exact nature of their Holocaust experiences, the extent of family bereavement and their country of origin) were found to be particularly potent predictors of not only their own psychological health but continue to be strongly influential in determining the psychological health of their descendants. Further highlighting the continuing influence of the Holocaust was the finding that number of Holocaust affected ancestors was the strongest demographic predictor of grandchild of survivor psychological health. Apart from demographic variables, the current thesis considered family environment dimensions which have been hypothesised to play a role in the transmission of the traumatic impact of the Holocaust from survivors to their descendants. Within the empirical study, parent-child attachment was found to be a key determinant in the transmission of Holocaust trauma from survivors to their children and insecure parent-child attachment continues to reverberate through the generations. In addition, survivors’ communication about the Holocaust and their Holocaust experiences to their children was found to be more influential than general communication within the family. Ten case studies (derived from the empirical study data set) are also provided; five Holocaust survivors, three children of survivors and two grandchildren of survivors. These cases add further to the picture of heterogeneity of the survivor and descendant populations in both experiences and adaptations. It is concluded that the legacy of the Holocaust continues to leave its mark on both its direct survivors and their descendants. Even two generations removed, the direct and indirect effects of the Holocaust have yet to be completely nullified. Research with Holocaust survivor families serves to highlight the differential impacts of state-based trauma and the ways in which its effects continue to be felt for generations. The revised and empirically tested Model of the Differential Impact of Holocaust Trauma across Three Generations presented at the conclusion of this thesis represents a further clarification of existing trauma theories as well as the first attempt at determining the relative importance of both cognitive, interpersonal/interfamilial interaction processes and demographic variables in post-trauma psychological health and transmission of traumatic impact.

Information transfer for multi-trauma patients on discharge from the emergency department : mixed-method narrative review

Aim. This paper is a report of a review conducted to identify (a) best practice in information transfer from the emergency department for multi-trauma patients; (b) conduits and barriers to information transfer in trauma care and related settings; and (c) interventions that have an impact on information communication at handover and beyond. Background. Information transfer is integral to effective trauma care, and communication breakdown results in important challenges to this. However, evidence of adequacy of structures and processes to ensure transfer of patient information through the acute phase of trauma care is limited. Data sources. Papers were sourced from a search of 12 online databases and scanning references from relevant papers for 1990–2009. Review methods. The review was conducted according to the University of York’s Centre for Reviews and Dissemination guidelines. Studies were included if they concerned issues that influenced information transfer for patients in healthcare settings. Results. Forty-five research papers, four literature reviews and one policy statement were found to be relevant to parts of the topic, but not all of it. The main issues emerging concerned the impact of communication breakdown in some form, and included communication issues within trauma team processes, lack of structure and clarity during handovers including missing, irrelevant and inaccurate information, distractions and poorly documented care. Conclusion. Many factors influence information transfer but are poorly identified in relation to trauma care. The measurement of information transfer, which is integral to patient handover, has not been the focus of research to date. Nonetheless, documented patient information is considered evidence of care and a resource that affects continuing care.

Person-independent facial expression detection using constrained local models

In automatic facial expression detection, very accurate registration is desired which can be achieved via a deformable model approach where a dense mesh of 60-70 points on the face is used, such as an active appearance model (AAM). However, for applications where manually labeling frames is prohibitive, AAMs do not work well as they do not generalize well to unseen subjects. As such, a more coarse approach is taken for person-independent facial expression detection, where just a couple of key features (such as face and eyes) are tracked using a Viola-Jones type approach. The tracked image is normally post-processed to encode for shift and illumination invariance using a linear bank of filters. Recently, it was shown that this preprocessing step is of no benefit when close to ideal registration has been obtained. In this paper, we present a system based on the Constrained Local Model (CLM) which is a generic or person-independent face alignment algorithm which gains high accuracy. We show these results against the LBP feature extraction on the CK+ and GEMEP datasets.

Toward a more robust facial expression recognition in occluded images using randomly sampled Gabor based templates

Occlusion is a big challenge for facial expression recognition (FER) in real-world situations. Previous FER efforts to address occlusion suffer from loss of appearance features and are largely limited to a few occlusion types and single testing strategy. This paper presents a robust approach for FER in occluded images and addresses these issues. A set of Gabor based templates is extracted from images in the gallery using a Monte Carlo algorithm. These templates are converted into distance features using template matching. The resulting feature vectors are robust to occlusion. Occluded eyes and mouth regions and randomly places occlusion patches are used for testing. Two testing strategies analyze the effects of these occlusions on the overall recognition performance as well as each facial expression. Experimental results on the Cohn-Kanade database confirm the high robustness of our approach and provide useful insights about the effects of occlusion on FER. Performance is also compared with previous approaches.

Automatically detecting pain in video through facial action units

In a clinical setting, pain is reported either through patient self-report or via an observer. Such measures are problematic as they are: 1) subjective, and 2) give no specific timing information. Coding pain as a series of facial action units (AUs) can avoid these issues as it can be used to gain an objective measure of pain on a frame-by-frame basis. Using video data from patients with shoulder injuries, in this paper, we describe an active appearance model (AAM)-based system that can automatically detect the frames in video in which a patient is in pain. This pain data set highlights the many challenges associated with spontaneous emotion detection, particularly that of expression and head movement due to the patient's reaction to pain. In this paper, we show that the AAM can deal with these movements and can achieve significant improvements in both the AU and pain detection performance compared to the current-state-of-the-art approaches which utilize similarity-normalized appearance features only.

Frequency decomposition techniques for increased discriminative 3D facial information capture

Eigen-based techniques and other monolithic approaches to face recognition have long been a cornerstone in the face recognition community due to the high dimensionality of face images. Eigen-face techniques provide minimal reconstruction error and limit high-frequency content while linear discriminant-based techniques (fisher-faces) allow the construction of subspaces which preserve discriminatory information. This paper presents a frequency decomposition approach for improved face recognition performance utilising three well-known techniques: Wavelets; Gabor / Log-Gabor; and the Discrete Cosine Transform. Experimentation illustrates that frequency domain partitioning prior to dimensionality reduction increases the information available for classification and greatly increases face recognition performance for both eigen-face and fisher-face approaches.

What are the real costs of major trauma?

Background This economic evaluation reports the results of a detailed study of the cost of major trauma treated at Princess Alexandra Hospital (PAH), Australia. Methods A bottom-up approach was used to collect and aggregate the direct and indirect costs generated by a sample of 30 inpatients treated for major trauma at PAH in 2004. Major trauma was defined as an admission for Multiple Significant Trauma with an Injury Severity Score >15. Direct and indirect costs were amalgamated from three sources, (1) PAH inpatient costs, (2) Medicare Australia, and (3) a survey instrument. Inpatient costs included the initial episode of inpatient care including clinical and outpatient services and any subsequent representations for ongoing-related medical treatment. Medicare Australia provided an itemized list of pharmaceutical and ambulatory goods and services. The survey instrument collected out-of-pocket expenses and opportunity cost of employment forgone. Inpatient data obtained from a publically funded trauma registry were used to control for any potential bias in our sample. Costs are reported in Australian dollars for 2004 and 2008. Results The average direct and indirect costs of major trauma incurred up to 1-year postdischarge were estimated to be A$78,577 and A$24,273, respectively. The aggregate costs, for the State of Queensland, were estimated to range from A$86.1 million to $106.4 million in 2004 and from A$135 million to A$166.4 million in 2008. Conclusion These results demonstrate that (1) the costs of major trauma are significantly higher than previously reported estimates and (2) the cost of readmissions increased inpatient costs by 38.1%.

Facial expression recognition using facial movement features

Facial expression is an important channel for human communication and can be applied in many real applications. One critical step for facial expression recognition (FER) is to accurately extract emotional features. Current approaches on FER in static images have not fully considered and utilized the features of facial element and muscle movements, which represent static and dynamic, as well as geometric and appearance characteristics of facial expressions. This paper proposes an approach to solve this limitation using ‘salient’ distance features, which are obtained by extracting patch-based 3D Gabor features, selecting the ‘salient’ patches, and performing patch matching operations. The experimental results demonstrate high correct recognition rate (CRR), significant performance improvements due to the consideration of facial element and muscle movements, promising results under face registration errors, and fast processing time. The comparison with the state-of-the-art performance confirms that the proposed approach achieves the highest CRR on the JAFFE database and is among the top performers on the Cohn-Kanade (CK) database.

Improving the performance of facial expression recognition using dynamic, subtle and regional features

Human facial expression is a complex process characterized of dynamic, subtle and regional emotional features. State-of-the-art approaches on facial expression recognition (FER) have not fully utilized this kind of features to improve the recognition performance. This paper proposes an approach to overcome this limitation using patch-based ‘salient’ Gabor features. A set of 3D patches are extracted to represent the subtle and regional features, and then inputted into patch matching operations for capturing the dynamic features. Experimental results show a significant performance improvement of the proposed approach due to the use of the dynamic features. Performance comparison with pervious work also confirms that the proposed approach achieves the highest CRR reported to date on the JAFFE database and a top-level performance on the Cohn-Kanade (CK) database.

Evaluation of texture and geometry for dimensional facial expression recognition

Facial expression recognition (FER) algorithms mainly focus on classification into a small discrete set of emotions or representation of emotions using facial action units (AUs). Dimensional representation of emotions as continuous values in an arousal-valence space is relatively less investigated. It is not fully known whether fusion of geometric and texture features will result in better dimensional representation of spontaneous emotions. Moreover, the performance of many previously proposed approaches to dimensional representation has not been evaluated thoroughly on publicly available databases. To address these limitations, this paper presents an evaluation framework for dimensional representation of spontaneous facial expressions using texture and geometric features. SIFT, Gabor and LBP features are extracted around facial fiducial points and fused with FAP distance features. The CFS algorithm is adopted for discriminative texture feature selection. Experimental results evaluated on the publicly accessible NVIE database demonstrate that fusion of texture and geometry does not lead to a much better performance than using texture alone, but does result in a significant performance improvement over geometry alone. LBP features perform the best when fused with geometric features. Distributions of arousal and valence for different emotions obtained via the feature extraction process are compared with those obtained from subjective ground truth values assigned by viewers. Predicted valence is found to have a more similar distribution to ground truth than arousal in terms of covariance or Bhattacharya distance, but it shows a greater distance between the means.

Sparse temporal representations for facial expression recognition

In automatic facial expression recognition, an increasing number of techniques had been proposed for in the literature that exploits the temporal nature of facial expressions. As all facial expressions are known to evolve over time, it is crucially important for a classifier to be capable of modelling their dynamics. We establish that the method of sparse representation (SR) classifiers proves to be a suitable candidate for this purpose, and subsequently propose a framework for expression dynamics to be efficiently incorporated into its current formulation. We additionally show that for the SR method to be applied effectively, then a certain threshold on image dimensionality must be enforced (unlike in facial recognition problems). Thirdly, we determined that recognition rates may be significantly influenced by the size of the projection matrix \Phi. To demonstrate these, a battery of experiments had been conducted on the CK+ dataset for the recognition of the seven prototypic expressions - anger, contempt, disgust, fear, happiness, sadness and surprise - and comparisons have been made between the proposed temporal-SR against the static-SR framework and state-of-the-art support vector machine.