Incidental treatment effects of CBT on suicidal ideation and hopelessness

Background: Depression and alcohol misuse are among the most prevalent diagnoses in suicide fatalities. The risk posed by these disorders is exacerbated when they co-occur. Limited research has evaluated the effectiveness of common depression and alcohol treatments for the reduction of suicide vulnerability in individuals experiencing comorbidity. Methods: Participants with depressive symptoms and hazardous alcohol use were selected from two randomised controlled trials. They had received either a brief (1 session) intervention, or depression-focused cognitive behaviour therapy (CBT), alcohol-focused CBT, therapist-delivered integrated CBT, computer-delivered integrated CBT or person-centred therapy (PCT) over a 10-week period. Suicidal ideation, hopelessness, depression severity and alcohol consumption were assessed at baseline and 12-month follow-up. Results: Three hundred three participants were assessed at baseline and 12 months. Both suicidal ideation and hopelessness were associated with higher severity of depressive symptoms, but not with alcohol consumption. Suicidal ideation did not improve significantly at follow-up, with no differences between treatment conditions. Improvements in hopelessness differed between treatment conditions; hopelessness improved more in the CBT conditions compared to PCT and in single-focused CBT compared to integrated CBT. Limitations: Low retention rates may have impacted on the reliability of our findings. Combining data from two studies may have resulted in heterogeneity of samples between conditions. Conclusions: CBT appears to be associated with reductions in hopelessness in people with co-occurring depression and alcohol misuse, even when it is not the focus of treatment. Less consistent results were observed for suicidal ideation. Establishing specific procedures or therapeutic content for clinicians to monitor these outcomes may result in better management of individuals with higher vulnerability for suicide.

Adverse breast cancer treatment effects: The economic case for making rehabilitative programs standard of care

Purpose: The purpose of this work was to evaluate the patient-borne financial cost of common, adverse breast cancer treatment-associated effects, comparing cost across women with or without these side-effects. Methods: 287 Australian women diagnosed with early-stage breast cancer were prospectively followed starting at six months post-surgery for 12 months, with three-monthly assessment of detailed treatment-related side effects and their direct and indirect patient costs attributable to breast cancer. Bootstrapping statistics were used to analyze cost data and adjusted logistic regression was used to evaluate the association between costs and adverse events from breast cancer. Costs were inflated and converted from 2002 Australian to 2014 US dollars. Results: More than 90% of women experienced at least one adverse effect (i.e. post-surgical issue, reaction to radiotherapy, upper-body symptoms or reduced function, lymphedema, fatigue or weight gain). On average, women paid $5,636 (95%CI: $4,694, $6,577) in total costs. Women with any one of the following symptoms (fatigue, reduced upper-body function, upper-body symptoms) or women who report ≥4 adverse treatment-related effects, have 1.5 to nearly 4 times the odds of having higher healthcare costs than women who do not report these complaints (p<0.05). Conclusions: Women face substantial economic burden due to a range of treatment-related health problems, which may persist beyond the treatment period. Improving breast cancer care by incorporating prospective surveillance of treatment-related side effects, and strategies for prevention and treatment of concerns (e.g., exercise) has real potential for reducing patient-borne costs.

A Comparison of Methods for Describing Irregular Animal Growth and Testing for Treatment Effects

In many designed experiments with animals liveweight is recorded several times during the trial. Such data are commonly referred to as repeated measures data. An aim of such experiments is generally to compare the growth patterns for the applied treatments. This paper discusses some of the methods of analysing repeated measures data and illustrates the use of cubic smoothing splines to describe irregular cattle growth data. Animal production for a consuming world : proceedings of 9th Congress of the Asian-Australasian Association of Animal Production Societies [AAAP] and 23rd Biennial Conference of the Australian Society of Animal Production [ASAP] and 17th Annual Symposium of the University of Sydney, Dairy Research Foundation, [DRF]. 2-7 July 2000, Sydney, Australia.

Applications of Treatment Effects Models and Semiparametric Estimation

This thesis is composed of an introductory chapter and four applications each of them constituting an own chapter. The common element underlying each of the chapters is the econometric methodology. The applications rely mostly on the leading econometric techniques related to estimation of causal effects. The first chapter introduces the econometric techniques that are employed in the remaining chapters. Chapter 2 studies the effects of shocking news on student performance. It exploits the fact that the school shooting in Kauhajoki in 2008 coincided with the matriculation examination period of that fall. It shows that the performance of men declined due to the news of the school shooting. For women the similar pattern remains unobserved. Chapter 3 studies the effects of minimum wage on employment by employing the original Card and Krueger (1994; CK) and Neumark and Wascher (2000; NW) data together with the changes-in-changes (CIC) estimator. As the main result it shows that the employment effect of an increase in the minimum wage is positive for small fast-food restaurants and negative for big fast-food restaurants. Therefore, it shows that the controversial positive employment effect reported by CK is overturned for big fast-food restaurants and that the NW data are shown, in contrast to their original results, to provide support for the positive employment effect. Chapter 4 employs the state-specific U.S. data (collected by Cohen and Einav [2003; CE]) on traffic fatalities to re-evaluate the effects of seat belt laws on the traffic fatalities by using the CIC estimator. It confirms the CE results that on the average an implementation of a mandatory seat belt law results in an increase in the seat belt usage rate and a decrease in the total fatality rate. In contrast to CE, it also finds evidence on compensating-behavior theory, which is observed especially in the states by the border of the U.S. Chapter 5 studies the life cycle consumption in Finland, with the special interest laid on the baby boomers and the older households. It shows that the baby boomers smooth their consumption over the life cycle more than other generations. It also shows that the old households smoothed their life cycle consumption more as a result of the recession in the 1990s, compared to young households.

Using heat treatment effects and EBSD analysis to tailor microstructure of hybrid Mg nanocomposite for enhanced overall mechanical response

In this study, a detailed investigation on the effect of heat treatment on the microstructural characteristics, texture evolution and mechanical properties of Mg-(5.6Ti+2.5B(4)C)(BM) hybrid nanocomposite is presented. Optimised heat treatment parameters, namely, heat treatment temperature and heat treatment time, were first identified through grain size and microhardness measurements. Initially, heat treatment of composites was conducted at temperature range between 100 and 300 degrees C for 1 h. Based on optical microscopic analysis and microhardness measurements, it was evident that significant grain growth and reduction in microhardness occurred for temperatures > 200 degrees C. The cutoff temperature that caused significant grain growth/matrix softening was thus identified. Second, at constant temperature (200 degrees C), the effect of variation of heat treatment time was carried out (ranging between 1 and 5 h) so as to identify the range wherein increase in average grain size and reduction in microhardness occurred. Furthering the study, the effect of optimised heat treatment parameters (200 degrees C, 5 h) on the microstructural texture evolution and hence, on the tensile and compressive properties of the Mg-(5.6Ti+2.5B(4)C)(BM) hybrid nanocomposite was carried out. From electron backscattered diffraction (EBSD) analysis, it was identified that the optimised heat treatment resulted in recrystallisation and residual stress relaxation, as evident from the presence of similar to 87% strain free grains, when compared to that observed in the non-heat treated/as extruded condition (i.e. 2.2 times greater than in the as extruded condition). For the heat treated composite, under both tensile and compressive loads, a significant improvement in fracture strain values (similar to 60% increase) was observed when compared to that of the non-heat treated counterpart, with similar to 20% reduction in yield strength. Based on structure-property correlation, the change in mechanical characteristics is identified to be due to: (1) the presence of less stressed matrix/reinforcement interface due to the relief of residual stresses and (2) texture weakening due to matrix recrystallisation effects, both arising due to heat treatment.

Essays in partial identification and applications to treatment effects and policy evaluation.

Dans cette thèse, je me suis interessé à l’identification partielle des effets de traitements dans différents modèles de choix discrets avec traitements endogènes. Les modèles d’effets de traitement ont pour but de mesurer l’impact de certaines interventions sur certaines variables d’intérêt. Le type de traitement et la variable d’intérêt peuvent être défini de manière générale afin de pouvoir être appliqué à plusieurs différents contextes. Il y a plusieurs exemples de traitement en économie du travail, de la santé, de l’éducation, ou en organisation industrielle telle que les programmes de formation à l’emploi, les techniques médicales, l’investissement en recherche et développement, ou l’appartenance à un syndicat. La décision d’être traité ou pas n’est généralement pas aléatoire mais est basée sur des choix et des préférences individuelles. Dans un tel contexte, mesurer l’effet du traitement devient problématique car il faut tenir compte du biais de sélection. Plusieurs versions paramétriques de ces modèles ont été largement étudiées dans la littérature, cependant dans les modèles à variation discrète, la paramétrisation est une source importante d’identification. Dans un tel contexte, il est donc difficile de savoir si les résultats empiriques obtenus sont guidés par les données ou par la paramétrisation imposée au modèle. Etant donné, que les formes paramétriques proposées pour ces types de modèles n’ont généralement pas de fondement économique, je propose dans cette thèse de regarder la version nonparamétrique de ces modèles. Ceci permettra donc de proposer des politiques économiques plus robustes. La principale difficulté dans l’identification nonparamétrique de fonctions structurelles, est le fait que la structure suggérée ne permet pas d’identifier un unique processus générateur des données et ceci peut être du soit à la présence d’équilibres multiples ou soit à des contraintes sur les observables. Dans de telles situations, les méthodes d’identifications traditionnelles deviennent inapplicable d’où le récent développement de la littérature sur l’identification dans les modèles incomplets. Cette littérature porte une attention particuliere à l’identification de l’ensemble des fonctions structurelles d’intérêt qui sont compatibles avec la vraie distribution des données, cet ensemble est appelé : l’ensemble identifié. Par conséquent, dans le premier chapitre de la thèse, je caractérise l’ensemble identifié pour les effets de traitements dans le modèle triangulaire binaire. Dans le second chapitre, je considère le modèle de Roy discret. Je caractérise l’ensemble identifié pour les effets de traitements dans un modèle de choix de secteur lorsque la variable d’intérêt est discrète. Les hypothèses de sélection du secteur comprennent le choix de sélection simple, étendu et généralisé de Roy. Dans le dernier chapitre, je considère un modèle à variable dépendante binaire avec plusieurs dimensions d’hétérogéneité, tels que les jeux d’entrées ou de participation. je caractérise l’ensemble identifié pour les fonctions de profits des firmes dans un jeux avec deux firmes et à information complète. Dans tout les chapitres, l’ensemble identifié des fonctions d’intérêt sont écrites sous formes de bornes et assez simple pour être estimées à partir des méthodes d’inférence existantes.

High pressure/thermal treatment effects on the texture of beef muscle

The effects of high pressure (to 800 MPa) applied at different temperatures (20-70 degreesC) for 20 min on beef post-rigor longissimus dorsi texture were studied. Texture profile analysis showed that when heated at ambient pressure there was the expected increase in hardness with increasing temperature and when pressure was applied at room temperature there was again the expected increase in hardness with increasing pressure. Similar results to those found at ambient temperature were found when pressure was applied at 40 degreesC. However, at higher temperatures, 60 and 70 degreesC it was found that pressures of 200 MPa caused large and significant decreases in hardness. The results found for hardness were mirrored by those for gumminess and chewiness. To further understand the changes in texture observed, intact beef longissimus dorsi samples and extracted myofibrils were both subjected to differential scanning calorimetry after being subjected to the same pressure/temperature regimes. As expected collagen was reasonably inert to pressure and only at temperatures of 60-70 degreesC was it denatured/unfolded. However, myosin was relatively easily unfolded by both pressure and temperature and when pressure denatured a new and modified structure was formed of low thermal stability. Although this new structure had low thermal stability at ambient pressure it still formed in both the meat and myofibrils when pressure was applied at 60 degreesC. It seems unlikely that structurally induced changes can be a major cause of the significant loss of hardness observed when beef is treated at high temperature (60-70 degreesC) and 200 MPa and it is suggested that accelerated proteolysis under these conditions is the major cause. (C) 2004 Elsevier Ltd. All rights reserved.

Partially identified treatment effects under imperfect compliance: the case of domestic violence

The Minneapolis Domestic Violence Experiment (MDVE) is a randomized social experiment with imperfect compliance which has been extremely influential in how police officers respond to misdemeanor domestic violence. This paper re-examines data from the MDVE, using recent literature on partial identification to find recidivism associated with a policy that arrests misdemeanor domestic violence suspects rather than not arresting them. Using partially identified bounds on the average treatment effect I find that arresting rather than not arresting suspects can potentially reduce recidivism by more than two-and-a-half times the corresponding intent-to-treat estimate and more than two times the corresponding local average treatment effect, even when making minimal assumptions on counterfactuals.

Enhancing the recovery of tiger nut (Cyperus esculentus) oil by mechanical pressing: moisture content, particle size, high pressure and enzymatic pre-treatment effects

Tiger nut (Cyperus esculentus) tuber contains oil that is high in monounsaturated fatty acids, and this oil makes up about 23% of the tuber. The study aimed at evaluating the impact of several factors and enzymatic pre-treatment on the recovery of pressed tiger nut oil. Smaller particles were more favourable for pressing. High pressure pre-treatment did not increase oil recovery but enzymatic treatment did. The highest yield obtained by enzymatic treatment prior to mechanical extraction was 33 % on a dry defatted basis, which represents a recovery of 90 % of the oil. Tiger nut oil consists mainly of oleic acid; its acid and peroxide values reflect the high stability of the oil.

Likelihood estimate of treatment effects under selection bias

We consider methods for estimating causal effects of treatment in the situation where the individuals in the treatment and the control group are self selected, i.e., the selection mechanism is not randomized. In this case, simple comparison of treated and control outcomes will not generally yield valid estimates of casual effects. The propensity score method is frequently used for the evaluation of treatment effect. However, this method is based onsome strong assumptions, which are not directly testable. In this paper, we present an alternative modeling approachto draw causal inference by using share random-effect model and the computational algorithm to draw likelihood based inference with such a model. With small numerical studies and a real data analysis, we show that our approach gives not only more efficient estimates but it is also less sensitive to model misspecifications, which we consider, than the existing methods.

Bounds on functionals of the distribution treatment effects

Bounds on the distribution function of the sum of two random variables with known marginal distributions obtained by Makarov (1981) can be used to bound the cumulative distribution function (c.d.f.) of individual treatment effects. Identification of the distribution of individual treatment effects is important for policy purposes if we are interested in functionals of that distribution, such as the proportion of individuals who gain from the treatment and the expected gain from the treatment for these individuals. Makarov bounds on the c.d.f. of the individual treatment effect distribution are pointwise sharp, i.e. they cannot be improved in any single point of the distribution. We show that the Makarov bounds are not uniformly sharp. Specifically, we show that the Makarov bounds on the region that contains the c.d.f. of the treatment effect distribution in two (or more) points can be improved, and we derive the smallest set for the c.d.f. of the treatment effect distribution in two (or more) points. An implication is that the Makarov bounds on a functional of the c.d.f. of the individual treatment effect distribution are not best possible.

Inequality treatment effects

This paper presents semiparametric estimators for treatment effects parameters when selection to treatment is based on observable characteristics. The parameters of interest in this paper are those that capture summarized distributional effects of the treatment. In particular, the focus is on the impact of the treatment calculated by differences in inequality measures of the potential outcomes of receiving and not receiving the treatment. These differences are called here inequality treatment effects. The estimation procedure involves a first non-parametric step in which the probability of receiving treatment given covariates, the propensity-score, is estimated. Using the reweighting method to estimate parameters of the marginal distribution of potential outcomes, in the second step weighted sample versions of inequality measures are.computed. Calculations of semiparametric effciency bounds for inequality treatment effects parameters are presented. Root-N consistency, asymptotic normality, and the achievement of the semiparametric efficiency bound are shown for the semiparametric estimators proposed. A Monte Carlo exercise is performed to investigate the behavior in finite samples of the estimator derived in the paper.

Efficient semiparametric estimation of quantile treatment effects

This paper presents calculations of semiparametric efficiency bounds for quantile treatment effects parameters when se1ection to treatment is based on observable characteristics. The paper also presents three estimation procedures forthese parameters, alI ofwhich have two steps: a nonparametric estimation and a computation ofthe difference between the solutions of two distinct minimization problems. Root-N consistency, asymptotic normality, and the achievement ofthe semiparametric efficiency bound is shown for one ofthe three estimators. In the final part ofthe paper, an empirical application to a job training program reveals the importance of heterogeneous treatment effects, showing that for this program the effects are concentrated in the upper quantiles ofthe earnings distribution.

Heat-treatment effects on the magnetic response of superconducting mesoscopic samples

The use of chemical methods in the synthesis of high-quality and small-size polycrystalline samples has been increased in recent years. In this work, a chemical route based on an aqueous precursor solution of metals followed by the addition of a water-soluble polymer formed by ethylenediaminetetraacetic acid (EDTA) and ethylene glycol (EG) was tested to produce superconducting mesoscopic YBa(2)Cu(3)O(7-gamma) samples. Different conditions of heat treatments and the effects of argon and oxygen atmospheres during the calcination steps were traced using X-ray diffraction (XRD), scanning electron microscopy (SEM) and magnetic measurements. (C) 2008 Elsevier B. V. All rights reserved.