Psychological interventions for alcohol misuse among people with co-occurring depression or anxiety disorders: A systematic review

Abstract OBJECTIVE: Depression, anxiety and alcohol misuse frequently co-occur. While there is an extensive literature reporting on the efficacy of psychological treatments that target depression, anxiety or alcohol misuse separately, less research has examined treatments that address these disorders when they co-occur. We conducted a systematic review to determine whether psychological interventions that target alcohol misuse among people with co-occurring depressive or anxiety disorders are effective. DATA SOURCES: We systematically searched the PubMed and PsychINFO databases from inception to March 2010. Individual searches in alcohol, depression and anxiety were conducted, and were limited to 'human' published 'randomized controlled trials' or 'sequential allocation' articles written in English. STUDY SELECTION: We identified randomized controlled trials that compared manual guided psychological interventions for alcohol misuse among individuals with depressive or anxiety disorders. Of 1540 articles identified, eight met inclusion criteria for the review. DATA EXTRACTION: From each study, we recorded alcohol and mental health outcomes, and other relevant clinical factors including age, gender ratio, follow-up length and drop-out rates. Quality of studies was also assessed. DATA SYNTHESIS: Motivational interviewing and cognitive-behavioral interventions were associated with significant reductions in alcohol consumption and depressive and/or anxiety symptoms. Although brief interventions were associated with significant improvements in both mental health and alcohol use variables, longer interventions produced even better outcomes. CONCLUSIONS: There is accumulating evidence for the effectiveness of motivational interviewing and cognitive behavior therapy for people with co-occurring alcohol and depressive or anxiety disorders.

Detection versus false alarm characterisation of a vision-based airborne dim-target collision detection system

This paper presents a preliminary flight test based detection range versus false alarm performance characterisation of a morphological-hidden Markov model filtering approach to vision-based airborne dim-target collision detection. On the basis of compelling in-flight collision scenario data, we calculate system operating characteristic (SOC) curves that concisely illustrate the detection range versus false alarm rate performance design trade-offs. These preliminary SOC curves provide a more complete dim-target detection performance description than previous studies (due to the experimental difficulties involved, previous studies have been limited to very short flight data sample sets and hence have not been able to quantify false alarm behaviour). The preliminary investigation here is based on data collected from 4 controlled collision encounters and supporting non-target flight data. This study suggests head-on detection ranges of approximately 2.22 km under blue sky background conditions (1.26 km in cluttered background conditions), whilst experiencing false alarms at a rate less than 1.7 false alarms/hour (ie. less than once every 36 minutes). Further data collection is currently in progress.

The use of semantic priming as a paradigm for the detection of faking on self-report psychological tests

It is recognised that individuals do not always respond honestly when completing psychological tests. One of the foremost issues for research in this area is the inability to detect individuals attempting to fake. While a number of strategies have been identified in faking, a commonality of these strategies is the latent role of long term memory. Seven studies were conducted in order to examine whether it is possible to detect the activation of faking related cognitions using a lexical decision task. Study 1 found that engagement with experiential processing styles predicted the ability to fake successfully, confirming the role of associative processing styles in faking. After identifying appropriate stimuli for the lexical decision task (Studies 2A and 2B), Studies 3 to 5 examined whether a cognitive state of faking could be primed and subsequently identified, using a lexical decision task. Throughout the course of these studies, the experimental methodology was increasingly refined in an attempt to successfully identify the relevant priming mechanisms. The results were consistent and robust throughout the three priming studies: faking good on a personality test primed positive faking related words in the lexical decision tasks. Faking bad, however, did not result in reliable priming of negative faking related cognitions. To more completely address potential issues with the stimuli and the possible role of affective priming, two additional studies were conducted. Studies 6A and 6B revealed that negative faking related words were more arousing than positive faking related words, and that positive faking related words were more abstract than negative faking related words and neutral words. Study 7 examined whether the priming effects evident in the lexical decision tasks occurred as a result of an unintentional mood induction while faking the psychological tests. Results were equivocal in this regard. This program of research aligned the fields of psychological assessment and cognition to inform the preliminary development and validation of a new tool to detect faking. Consequently, an implicit technique to identify attempts to fake good on a psychological test has been identified, using long established and robust cognitive theories in a novel and innovative way. This approach represents a new paradigm for the detection of individuals responding strategically to psychological testing. With continuing development and validation, this technique may have immense utility in the field of psychological assessment.

Neuropsychological development in children with early and continuously treated phenylketonuria : association with biochemical markers

PKU is a genetically inherited inborn error of metabolism caused by a deficiency of the enzyme phenylalanine hydroxylase. The failure of this enzyme causes incomplete metabolism of protein ingested in the diet, specifically the conversion of one amino acid, phenylalanine, to tyrosine, which is a precursor to the neurotransmitter dopamine. Rising levels of phenylalanine is toxic to the developing brain, disrupting the formation of white matter tracts. The impact of tyrosine deficiency is not as well understood, but is hypothesized to lead to a low dopamine environment for the developing brain. Detection in the newborn period and continuous treatment (a low protein phe-restricted diet supplemented with phenylalanine-free protein formulas) has resulted in children with early and continuously treated PKU now developing normal I.Q. However, deficits in executive function (EF) are common, leading to a rate of Attention Deficit Hyperactivity Disorder (ADHD) up to five times the norm. EF worsens with exposure to higher phenylalanine levels, however recent research has demonstrated that a high phenylalanine to tyrosine ratio (phenylalanine:tyrosine ratio), which is hypothesised to lead to poorer dopamine function, has a more negative impact on EF than phenylalanine levels alone. Research and treatment of PKU is currently phenylalanine-focused, with little investigation of the impact of tyrosine on neuropsychological development. There is no current consensus as to the veracity of tyrosine monitoring or treatment in this population. Further, the research agenda in this population has demonstrated a primary focus on EF impairment alone, even though there may be additional neuropsychological skills compromised (e.g., mood, visuospatial deficits). The aim of this PhD research was to identify residual neuropsychological deficits in a cohort of children with early and continuously treated phenylketonuria, at two time points in development (early childhood and early adolescence), separated by eight years. In addition, this research sought to determine which biochemical markers were associated with neuropsychological impairments. A clinical practice survey was also undertaken to ascertain the current level of monitoring/treatment of tyrosine in this population. Thirteen children with early and continuously treated PKU were tested at mean age 5.9 years and again at mean age 13.95 years on several neuropsychological measures. Four children with hyperphenylalaninemia (a milder version of PKU) were also tested at both time points and provide a comparison group in analyses. Associations between neuropsychological function and biochemical markers were analysed. A between groups analysis in adolescence was also conducted (children with PKU compared to their siblings) on parent report measures of EF and mood. Minor EF impairments were evident in the PKU group by age 6 years and these persisted into adolescence. Life-long exposure to high phenylalanine:tyrosine ratio and/or low tyrosine independent of phenylalanine were significantly associated with EF impairments at both time points. Over half the children with PKU showed severe impairment on a visuospatial task, and this was associated only with concurrent levels of tyrosine in adolescence. Children with PKU also showed a statistically significant decline in a language comprehension task from 6 years to adolescence (going from normal to subnormal), this deficit was associated with lifetime levels of phenylalanine. In comparison, the four children with hyperphenylalaninemia demonstrated normal function at both time points, across all measures. No statistically significant differences were detected between children with PKU and their siblings on the parent report of EF and mood. However, depressive symptoms were significantly correlated with: EF; long term high phe:tyr exposure; and low tyrosine levels independent of phenylalanine. The practice survey of metabolic clinics from 12 countries indicated a high level of variability in terms of monitoring/treatment of tyrosine in this population. Whilst over 80% of clinics surveyed routinely monitored tyrosine levels in their child patients, 25% reported treatment strategies to increase tyrosine (and thereby lower the phenylalanine:tyrosine ratio) under a variety of patient presentation conditions. Overall, these studies have shown that EF impairments associated with PKU provide support for the dopamine-deficiency model. A language comprehension task showed a different trajectory, serving a timely reminder that non-EF functions also remain vulnerable in this population; and that normal function in childhood does not guarantee normal function by adolescence. Mood impairments were associated with EF impairments as well as long term measures of phenylalanine:tyrosine and/or tyrosine. The implications of this research for enhanced clinical guidelines are discussed given varied current practice.

Detection of bacteriophage and respiratory viruses in droplets

Influenza is a widespread disease occurring in seasonal epidemics, and each year is responsible for up to 500,000 deaths worldwide. Influenza can develop into strains which cause severe symptoms and high mortality rates, and could potentially reach pandemic status if the virus’ properties allow easy transmission. Influenza is transmissible via contact with the virus, either directly (infected people) or indirectly (contaminated objects); via reception of large droplets over short distances (one metre or less); or through inhalation of aerosols containing the virus expelled by infected individuals during respiratory activities, that can remain suspended in the air and travel distances of more than one metre (the aerosol route). Aerosol transmission of viruses involves three stages: production of the droplets containing viruses; transport of the droplets and ability of a virus to remain intact and infectious; and reception of the droplets (via inhalation). Our understanding of the transmission of influenza viruses via the aerosol route is poor, and thus our ability to prevent a widespread outbreak is limited. This study explored the fate of viruses in droplets by investigating the effects of some physical factors on the recovery of both a bacteriophage model and influenza virus. Experiments simulating respiratory droplets were carried out using different types of droplets, generated from a commonly used water-like matrix, and also from an ‘artificial mucous’ matrix which was used to more closely resemble respiratory fluids. To detect viruses in droplets, we used the traditional plaque assay techniques, and also a sensitive, quantitative PCR assay specifically developed for this study. Our results showed that the artificial mucous suspension enhanced the recovery of infectious bacteriophage. We were able to report detection limits of infectious bacteriophage (no bacteriophage was detected by the plaque assay when aerosolised from a suspension of 103 PFU/mL, for three of the four droplet types tested), and that bacteriophage could remain infectious in suspended droplets for up to 20 minutes. We also showed that the nested real-time PCR assay was able to detect the presence of bacteriophage RNA where the plaque assay could not detect any intact particles. Finally, when applying knowledge from the bacteriophage experiments, we reported the quantitative recoveries of influenza viruses in droplets, which were more consistent and stable than we had anticipated. Influenza viruses can be detected up to 20 minutes (after aerosolisation) in suspended aerosols and possibly beyond. It also was detectable from nebulising suspensions with relatively low concentrations of viruses.

Classification of packet contents for malware detection

Many existing schemes for malware detection are signature-based. Although they can effectively detect known malwares, they cannot detect variants of known malwares or new ones. Most network servers do not expect executable code in their in-bound network traffic, such as on-line shopping malls, Picasa, Youtube, Blogger, etc. Therefore, such network applications can be protected from malware infection by monitoring their ports to see if incoming packets contain any executable contents. This paper proposes a content-classification scheme that identifies executable content in incoming packets. The proposed scheme analyzes the packet payload in two steps. It first analyzes the packet payload to see if it contains multimedia-type data (such as . If not, then it classifies the payload either as text-type (such as or executable. Although in our experiments the proposed scheme shows a low rate of false negatives and positives (4.69% and 2.53%, respectively), the presence of inaccuracies still requires further inspection to efficiently detect the occurrence of malware. In this paper, we also propose simple statistical and combinatorial analysis to deal with false positives and negatives.

Fat and thin adaptive HMM filters for vision based detection of moving targets

Computer vision is an attractive solution for uninhabited aerial vehicle (UAV) collision avoidance, due to the low weight, size and power requirements of hardware. A two-stage paradigm has emerged in the literature for detection and tracking of dim targets in images, comprising of spatial preprocessing, followed by temporal filtering. In this paper, we investigate a hidden Markov model (HMM) based temporal filtering approach. Specifically, we propose an adaptive HMM filter, in which the variance of model parameters is refined as the quality of the target estimate improves. Filters with high variance (fat filters) are used for target acquisition, and filters with low variance (thin filters) are used for target tracking. The adaptive filter is tested in simulation and with real data (video of a collision-course aircraft). Our test results demonstrate that our adaptive filtering approach has improved tracking performance, and provides an estimate of target heading not present in previous HMM filtering approaches.

University students’ depression : a cross-cultural investigation

Australian, Iranian and Portuguese university students (N = 967) completed University Students Depression Inventory (USDI; Khawaja & Bryden, 2006) in English, Persian, and Portuguese languages respectively. A series of MANOVA were used to examine differences in depression symptoms as an effect of the country and demographic variables. Interactions were also examined. The results indicated that country, gender, and year level had some impact on the depressive symptoms of the university students. Australian students were more depressed than the Iranian and Portuguese students, while Iranian students were more depressed than the Portuguese students. Subscales of USDI: Lethargy, Motivation, and Cognitive/Emotional were also used to compare the depressive symptoms of students. The Australian female students reported a significantly higher level of lethargy than their male counterparts. Similarly, the first year male students from Iran were significantly more lethargic than the first year Iranian female students. Iranian and Portuguese male students, compared to the female students of these countries, experienced a lower level of motivation. The Australian and Iranian students, compared to the Portuguese students, reported a significantly higher level of cognitive and affective symptoms. The scores on the Cognitive/Emotional subscale increased with the year level. Differences among students’ depression are described and implications discussed.

The relationship between abdominal obesity and depression in the general population : a systematic review and meta-analysis

Obesity has been widely regarded as a public health concern because of its adverse impact on individuals’ health. Systematic reviews have been published in examining the effect of obesity on depression, but with major emphasis on general obesity as measured by the body mass index. Despite a stronger effect of abdominal obesity on individuals’ physical health outcomes, to our best knowledge, no systematic review was undertaken with regard to the relationship between abdominal obesity and depression. This paper reports the results of a systematic review and meta-analysis of cross-sectional studies examining the relationship between abdominal obesity and depression in a general population. Multiple electronic databases were searched until the end of September 2009. 15 articles were systematically reviewed and meta-analyzed. The analysis showed that the odds ratio of having depression for individuals with abdominal obesity was 1.38 (95% CI, 1.22–1.57) as compared to those who are not obese. Furthermore, it was found that this relationship did not vary with potential confounders including gender, age, measurement of depression and abdominal obesity, and study quality.

A taint marking approach to confidentiality violation detection

This article presents a novel approach to confidentiality violation detection based on taint marking. Information flows are dynamically tracked between applications and objects of the operating system such as files, processes and sockets. A confidentiality policy is defined by labelling sensitive information and defining which information may leave the local system through network exchanges. Furthermore, per application profiles can be defined to restrict the sets of information each application may access and/or send through the network. In previous works, we focused on the use of mandatory access control mechanisms for information flow tracking. In this current work, we have extended the previous information flow model to track network exchanges, and we are able to define a policy attached to network sockets. We show an example application of this extension in the context of a compromised web browser: our implementation detects a confidentiality violation when the browser attempts to leak private information to a remote host over the network.

A suspicious behaviour detection using a context space model for smart surveillance systems

Video surveillance systems using Closed Circuit Television (CCTV) cameras, is one of the fastest growing areas in the field of security technologies. However, the existing video surveillance systems are still not at a stage where they can be used for crime prevention. The systems rely heavily on human observers and are therefore limited by factors such as fatigue and monitoring capabilities over long periods of time. This work attempts to address these problems by proposing an automatic suspicious behaviour detection which utilises contextual information. The utilisation of contextual information is done via three main components: a context space model, a data stream clustering algorithm, and an inference algorithm. The utilisation of contextual information is still limited in the domain of suspicious behaviour detection. Furthermore, it is nearly impossible to correctly understand human behaviour without considering the context where it is observed. This work presents experiments using video feeds taken from CAVIAR dataset and a camera mounted on one of the buildings Z-Block) at the Queensland University of Technology, Australia. From these experiments, it is shown that by exploiting contextual information, the proposed system is able to make more accurate detections, especially of those behaviours which are only suspicious in some contexts while being normal in the others. Moreover, this information gives critical feedback to the system designers to refine the system.

Acoustic component detection for automatic species recognition in environmental monitoring

Automatic species recognition plays an important role in assisting ecologists to monitor the environment. One critical issue in this research area is that software developers need prior knowledge of specific targets people are interested in to build templates for these targets. This paper proposes a novel approach for automatic species recognition based on generic knowledge about acoustic events to detect species. Acoustic component detection is the most critical and fundamental part of this proposed approach. This paper gives clear definitions of acoustic components and presents three clustering algorithms for detecting four acoustic components in sound recordings; whistles, clicks, slurs, and blocks. The experiment result demonstrates that these acoustic component recognisers have achieved high precision and recall rate.

Evaluating automatic road detection across a large aerial imagery collection

The automated extraction of roads from aerial imagery can be of value for tasks including mapping, surveillance and change detection. Unfortunately, there are no public databases or standard evaluation protocols for evaluating these techniques. Many techniques are further hindered by a reliance on manual initialisation, making large scale application of the techniques impractical. In this paper, we present a public database and evaluation protocol for the evaluation of road extraction algorithms, and propose an improved automatic seed finding technique to initialise road extraction, based on a combination of geometric and colour features.

Loop closure detection on a suburban road network using a continuous appearance-based trajectory

This paper presents a novel technique for performing SLAM along a continuous trajectory of appearance. Derived from components of FastSLAM and FAB-MAP, the new system dubbed Continuous Appearance-based Trajectory SLAM (CAT-SLAM) augments appearancebased place recognition with particle-filter based ‘pose filtering’ within a probabilistic framework, without calculating global feature geometry or performing 3D map construction. For loop closure detection CAT-SLAM updates in constant time regardless of map size. We evaluate the effectiveness of CAT-SLAM on a 16km outdoor road network and determine its loop closure performance relative to FAB-MAP. CAT-SLAM recognizes 3 times the number of loop closures for the case where no false positives occur, demonstrating its potential use for robust loop closure detection in large environments.