Does low self-esteem predict depression and anxiety? A meta-analysis of longitudinal studies

Low self-esteem and depression are strongly related, but there is not yet consistent evidence on the nature of the relation. Whereas the vulnerability model states that low self-esteem contributes to depression, the scar model states that depression erodes self-esteem. Furthermore, it is unknown whether the models are specific for depression or whether they are also valid for anxiety. We evaluated the vulnerability and scar models of low self-esteem and depression, and low self-esteem and anxiety, by meta-analyzing the available longitudinal data (covering 77 studies on depression and 18 studies on anxiety). The mean age of the samples ranged from childhood to old age. In the analyses, we used a random-effects model and examined prospective effects between the variables, controlling for prior levels of the predicted variables. For depression, the findings supported the vulnerability model: The effect of self-esteem on depression (β = -.16) was significantly stronger than the effect of depression on self-esteem (β = -.08). In contrast, the effects between low self-esteem and anxiety were relatively balanced: Self-esteem predicted anxiety with β = -.10, and anxiety predicted self-esteem with β = -.08. Moderator analyses were conducted for the effect of low self-esteem on depression; these suggested that the effect is not significantly influenced by gender, age, measures of self-esteem and depression, or time lag between assessments. If future research supports the hypothesized causality of the vulnerability effect of low self-esteem on depression, interventions aimed at increasing self-esteem might be useful in reducing the risk of depression.

Accuracy and self correction of information received from an internet breast cancer list: content analysis.

OBJECTIVES: To determine the prevalence of false or misleading statements in messages posted by internet cancer support groups and whether these statements were identified as false or misleading and corrected by other participants in subsequent postings. DESIGN: Analysis of content of postings. SETTING: Internet cancer support group Breast Cancer Mailing List. MAIN OUTCOME MEASURES: Number of false or misleading statements posted from 1 January to 23 April 2005 and whether these were identified and corrected by participants in subsequent postings. RESULTS: 10 of 4600 postings (0.22%) were found to be false or misleading. Of these, seven were identified as false or misleading by other participants and corrected within an average of four hours and 33 minutes (maximum, nine hours and nine minutes). CONCLUSIONS: Most posted information on breast cancer was accurate. Most false or misleading statements were rapidly corrected by participants in subsequent postings.

The accuracy of self-reported medical history: A preliminary analysis of the promise of internet-based research in Inflammatory Bowel Diseases

BACKGROUND AND AIMS: Internet-based surveys provide a potentially important tool for Inflammatory Bowel Disease (IBD) research. The advantages include low cost, large numbers of participants, rapid study completion and less extensive infrastructure than traditional methods. The aim was to determine the accuracy of patient self-reporting in internet-based IBD research and identify predictors of greater reliability. METHODS: 197 patients from a tertiary care center answered an online survey concerning personal medical history and an evaluation of disease specific knowledge. Self-reported medical details were compared with data abstracted from medical records. Agreement was assessed by kappa (κ) statistics. RESULTS: Participants responded correctly with excellent agreement (κ=0.96-0.97) on subtype of IBD and history of surgery. The agreement was also excellent for colectomy (κ=0.88) and small bowel resection (κ=0.91), moderate for abscesses and fistulas (κ=0.60 and 0.63), but poor regarding partial colectomy (κ=0.39). Time since last colonoscopy was self-reported with better agreement (κ=0.84) than disease activity. For disease location/extent, moderate agreements at κ=69% and 64% were observed for patients with Crohn's disease and ulcerative colitis, respectively. Subjects who scored higher than the average in the IBD knowledge assessment were significantly more accurate about disease location than their complementary group (74% vs. 59%, p=0.02). CONCLUSION: This study demonstrates that IBD patients accurately report their medical history regarding type of disease and surgical procedures. More detailed medical information is less reliably reported. Disease knowledge assessment may help in identifying the most accurate individuals and could therefore serve as validity criteria. Internet-based surveys are feasible with high reliability about basic disease features only. However, the participants in this study were engaged at a tertiary center, which potentially leads to a bias and compromises generalization to an unfiltered patient group.

Initial orthodontic alignment effectiveness with self-ligating and conventional appliances: a network meta-analysis in practice.

Systematic reviews of well-designed trials constitute a high level of scientific evidence and are important for medical decision making. Meta-analysis facilitates integration of the evidence using a transparent and systematic approach, leading to a broader interpretation of treatment effectiveness and safety than can be attained from individual studies. Traditional meta-analyses are limited to comparing just 2 interventions concurrently and cannot combine evidence concerning multiple treatments. A relatively recent extension of the traditional meta-analytical approach is network meta-analysis, which allows, under certain assumptions, the quantitative synthesis of all evidence under a unified framework and across a network of all eligible trials. Network meta-analysis combines evidence from direct and indirect information via common comparators; interventions can therefore be ranked in terms of the analyzed outcome. In this article, the network meta-analysis approach is introduced in a nontechnical manner using a worked example on the treatment effectiveness of conventional and self-ligating appliances.

The 'triple contrast' method in experimental wound ballistics and backspatter analysis.

In practical forensic casework, backspatter recovered from shooters' hands can be an indicator of self-inflicted gunshot wounds to the head. In such cases, backspatter retrieved from inside the barrel indicates that the weapon found at the death scene was involved in causing the injury to the head. However, systematic research on the aspects conditioning presence, amount and specific patterns of backspatter is lacking so far. Herein, a new concept of backspatter investigation is presented, comprising staining technique, weapon and target medium: the 'triple contrast method' was developed, tested and is introduced for experimental backspatter analysis. First, mixtures of various proportions of acrylic paint for optical detection, barium sulphate for radiocontrast imaging in computed tomography and fresh human blood for PCR-based DNA profiling were generated (triple mixture) and tested for DNA quantification and short tandem repeat (STR) typing success. All tested mixtures yielded sufficient DNA that produced full STR profiles suitable for forensic identification. Then, for backspatter analysis, sealed foil bags containing the triple mixture were attached to plastic bottles filled with 10 % ballistic gelatine and covered by a 2-3-mm layer of silicone. To simulate backspatter, close contact shots were fired at these models. Endoscopy of the barrel inside revealed coloured backspatter containing typable DNA and radiographic imaging showed a contrasted bullet path in the gelatine. Cross sections of the gelatine core exhibited cracks and fissures stained by the acrylic paint facilitating wound ballistic analysis.

Facial self-mutilation: an analysis of published cases

OBJECTIVES Facial self-mutilation is rare. It is usually discussed from the psychiatric or psychoanalytic perspectives but has little prominence in general medical literature. Our objective was to describe facial self-mutilation in terms of its comorbidities, and to outline the different types of facial mutilation, as well as the basic approach to the patients with facial self-mutilation. METHODS We undertook a review of all published cases of facial self-mutilation (1960-2011). RESULTS We identified 200 published cases in 123 relevant papers. Four major groups of comorbidities emerged: psychiatric, neurological and hereditary disorders, and a group of patients without identified comorbidities. There were three general patterns of facial self-mutilation: (1) major and definitive mutilation, with the ocular globe as primary target--seen in patients with psychotic disorders; (2) stereotypical mutilation involving the oral cavity and of variable degree of severity, most often seen in patients with hereditary neuropathy or encephalopathy; (3) mild chronic self-mutilation, seen in patients with non-psychotic psychiatric disorders, acquired neurological disorders, and patients without comorbidities. About 20% of patients that mutilated their face also mutilated extra-facial structures. Patients with psychiatric conditions, especially those with psychotic disorders, had significantly higher (p<0.05) rates of permanent facial self-mutilation than others. Most treatment plans were very individually based, but some principles, such as prevention of irreversible loss of function and structure, or development of infection are applicable to all patients with facial self-mutilation. CONCLUSIONS Facial self-mutilation is a potentially severe manifestation of diverse conditions. Several aspects of facial self-mutilation remain to be fully characterised from a clinical perspective.

Endogenous Growth in the Presence of Informal Credit Markets: A Comparative Analysis Between Credit Rationing and Self-Revelation Regimes

This paper examines whether the presence of informal credit markets reduces the cost of credit rationing in terms of growth. In a dynamic general equilibrium framework, we assume that firms are heterogenous with different degrees of risk and households invest in human capital development. With the help of Indian household level data we show that the informal market reduces the cost of rationing by increasing the growth rate by 0.7 percent. This higher growth rate, in the presence of an informal sector, is due to the ability of the informal market to separate the high risk from the low risk firms thanks to better information. But even after such improvement we do not get the optimum outcome. The findings, based on our second question, suggest that the revelation of firms' type, based on incentive compatible pricing, can lead to almost 2 percent higher growth rate as compared to the credit rationing regime with informal sector.

An Institutional Analysis of Environmental Pollution Disputes in Taiwan: Cases of 'Self-Relief'

During the late 1980s and early 1990s in Taiwan, people's protests against environmental pollution often took the form of "self-relief," meaning that they attempted to fight polluters using their own resources, without relying on legal or administrative procedures. Why did such an extreme form of disputes become so widespread? What institutional changes did these movements bring about? These questions are analyzed using the analytical framework of "law and economics." Our research shows that "self-relief" functioned to a certain extent as a means of realizing quick compensation for victims, and for reflecting the opinions of local people concerning development projects; in addition, it served to promote the formulation of law and administrative systems. However, as it was based on direct negotiations between the parties concerned, the outcome of each dispute only reflected the transient balance of forces, and the experience gained in negotiations was not accumulated as a social norm.

Fault Tolerance Analysis and Self-Healing Strategy of Autonomous, Evolvable Hardware Systems

This paper presents an analysis of the fault tolerance achieved by an autonomous, fully embedded evolvable hardware system, which uses a combination of partial dynamic reconfiguration and an evolutionary algorithm (EA). It demonstrates that the system may self-recover from both transient and cumulative permanent faults. This self-adaptive system, based on a 2D array of 16 (4×4) Processing Elements (PEs), is tested with an image filtering application. Results show that it may properly recover from faults in up to 3 PEs, that is, more than 18% cumulative permanent faults. Two fault models are used for testing purposes, at PE and CLB levels. Two self-healing strategies are also introduced, depending on whether fault diagnosis is available or not. They are based on scrubbing, fitness evaluation, dynamic partial reconfiguration and in-system evolutionary adaptation. Since most of these adaptability features are already available on the system for its normal operation, resource cost for self-healing is very low (only some code additions in the internal microprocessor core)

Goal-oriented self-adaptive hp-strategies for finite element analysis of electromagnetic scattering and radiation problems

In this paper, a fully automatic goal-oriented hp-adaptive finite element strategy for open region electromagnetic problems (radiation and scattering) is presented. The methodology leads to exponential rates of convergence in terms of an upper bound of an user-prescribed quantity of interest. Thus, the adaptivity may be guided to provide an optimal error, not globally for the field in the whole finite element domain, but for specific parameters of engineering interest. For instance, the error on the numerical computation of the S-parameters of an antenna array, the field radiated by an antenna, or the Radar Cross Section on given directions, can be minimized. The efficiency of the approach is illustrated with several numerical simulations with two dimensional problem domains. Results include the comparison with the previously developed energy-norm based hp-adaptivity.

Voltage limitation analysis in strain-balanced InAs/GaAsN quantum dot solar cells applied to the intermediate band concept

Several attempts have been carried out to manufacture intermediate band solar cells (IBSC) by means of quantum dot (QD) superlattices. This novel photovoltaic concept allows the collection of a wider range of the sunlight spectrum in order to provide higher cell photocurrent while maintaining the open-circuit voltage (VOC) of the cell. In this work, we analyze InAs/GaAsN QD-IBSCs. In these cells, the dilute nitrogen in the barrier plays an important role for the strain-balance (SB) of the QD layer region that would otherwise create dislocations under the effect of the accumulated strain. The introduction of GaAsN SB layers allows increasing the light absorption in the QD region by multi-stacking more than 100 QD layers. The photo-generated current density (JL) versus VOC was measured under varied concentrated light intensity and temperature. We found that the VOC of the cell at 20 K is limited by the bandgap of the GaAsN barriers, which has important consequences regarding IBSC bandgap engineering that are also discussed in this work.

Self-organizing cultured neural networks: Image analysis techniques for longitudinal tracking and modeling of the underlying network structure

Esta tesis estudia la evolución estructural de conjuntos de neuronas como la capacidad de auto-organización desde conjuntos de neuronas separadas hasta que forman una red (clusterizada) compleja. Esta tesis contribuye con el diseño e implementación de un algoritmo no supervisado de segmentación basado en grafos con un coste computacional muy bajo. Este algoritmo proporciona de forma automática la estructura completa de la red a partir de imágenes de cultivos neuronales tomadas con microscopios de fase con una resolución muy alta. La estructura de la red es representada mediante un objeto matemático (matriz) cuyos nodos representan a las neuronas o grupos de neuronas y los enlaces son las conexiones reconstruidas entre ellos. Este algoritmo extrae también otras medidas morfológicas importantes que caracterizan a las neuronas y a las neuritas. A diferencia de otros algoritmos hasta el momento, que necesitan de fluorescencia y técnicas inmunocitoquímicas, el algoritmo propuesto permite el estudio longitudinal de forma no invasiva posibilitando el estudio durante la formación de un cultivo. Además, esta tesis, estudia de forma sistemática un grupo de variables topológicas que garantizan la posibilidad de cuantificar e investigar la progresión de las características principales durante el proceso de auto-organización del cultivo. Nuestros resultados muestran la existencia de un estado concreto correspondiente a redes con configuracin small-world y la emergencia de propiedades a micro- y meso-escala de la estructura de la red. Finalmente, identificamos los procesos físicos principales que guían las transformaciones morfológicas de los cultivos y proponemos un modelo de crecimiento de red que reproduce el comportamiento cuantitativamente de las observaciones experimentales. ABSTRACT The thesis analyzes the morphological evolution of assemblies of living neurons, as they self-organize from collections of separated cells into elaborated, clustered, networks. In particular, it contributes with the design and implementation of a graph-based unsupervised segmentation algorithm, having an associated very low computational cost. The processing automatically retrieves the whole network structure from large scale phase-contrast images taken at high resolution throughout the entire life of a cultured neuronal network. The network structure is represented by a mathematical object (a matrix) in which nodes are identified neurons or neurons clusters, and links are the reconstructed connections between them. The algorithm is also able to extract any other relevant morphological information characterizing neurons and neurites. More importantly, and at variance with other segmentation methods that require fluorescence imaging from immunocyto- chemistry techniques, our measures are non invasive and entitle us to carry out a fully longitudinal analysis during the maturation of a single culture. In turn, a systematic statistical analysis of a group of topological observables grants us the possibility of quantifying and tracking the progression of the main networks characteristics during the self-organization process of the culture. Our results point to the existence of a particular state corresponding to a small-world network configuration, in which several relevant graphs micro- and meso-scale properties emerge. Finally, we identify the main physical processes taking place during the cultures morphological transformations, and embed them into a simplified growth model that quantitatively reproduces the overall set of experimental observations.

Self-organizing cultured neural networks: Image analysis techniques for longitudinal tracking and modeling of the underlying network structure (versión actualizada)

Esta tesis estudia la evolución estructural de conjuntos de neuronas como la capacidad de auto-organización desde conjuntos de neuronas separadas hasta que forman una red (clusterizada) compleja. Esta tesis contribuye con el diseño e implementación de un algoritmo no supervisado de segmentación basado en grafos con un coste computacional muy bajo. Este algoritmo proporciona de forma automática la estructura completa de la red a partir de imágenes de cultivos neuronales tomadas con microscopios de fase con una resolución muy alta. La estructura de la red es representada mediante un objeto matemático (matriz) cuyos nodos representan a las neuronas o grupos de neuronas y los enlaces son las conexiones reconstruidas entre ellos. Este algoritmo extrae también otras medidas morfológicas importantes que caracterizan a las neuronas y a las neuritas. A diferencia de otros algoritmos hasta el momento, que necesitan de fluorescencia y técnicas inmunocitoquímicas, el algoritmo propuesto permite el estudio longitudinal de forma no invasiva posibilitando el estudio durante la formación de un cultivo. Además, esta tesis, estudia de forma sistemática un grupo de variables topológicas que garantizan la posibilidad de cuantificar e investigar la progresión de las características principales durante el proceso de auto-organización del cultivo. Nuestros resultados muestran la existencia de un estado concreto correspondiente a redes con configuracin small-world y la emergencia de propiedades a micro- y meso-escala de la estructura de la red. Finalmente, identificamos los procesos físicos principales que guían las transformaciones morfológicas de los cultivos y proponemos un modelo de crecimiento de red que reproduce el comportamiento cuantitativamente de las observaciones experimentales. ABSTRACT The thesis analyzes the morphological evolution of assemblies of living neurons, as they self-organize from collections of separated cells into elaborated, clustered, networks. In particular, it contributes with the design and implementation of a graph-based unsupervised segmentation algorithm, having an associated very low computational cost. The processing automatically retrieves the whole network structure from large scale phase-contrast images taken at high resolution throughout the entire life of a cultured neuronal network. The network structure is represented by a mathematical object (a matrix) in which nodes are identified neurons or neurons clusters, and links are the reconstructed connections between them. The algorithm is also able to extract any other relevant morphological information characterizing neurons and neurites. More importantly, and at variance with other segmentation methods that require fluorescence imaging from immunocyto- chemistry techniques, our measures are non invasive and entitle us to carry out a fully longitudinal analysis during the maturation of a single culture. In turn, a systematic statistical analysis of a group of topological observables grants us the possibility of quantifying and tracking the progression of the main networks characteristics during the self-organization process of the culture. Our results point to the existence of a particular state corresponding to a small-world network configuration, in which several relevant graphs micro- and meso-scale properties emerge. Finally, we identify the main physical processes taking place during the cultures morphological transformations, and embed them into a simplified growth model that quantitatively reproduces the overall set of experimental observations.