A model for the time-order error in contrast discrimination.

Trials in a temporal two-interval forced-choice discrimination experiment consist of two sequential intervals presenting stimuli that differ from one another as to magnitude along some continuum. The observer must report in which interval the stimulus had a larger magnitude. The standard difference model from signal detection theory analyses poses that order of presentation should not affect the results of the comparison, something known as the balance condition (J.-C. Falmagne, 1985, in Elements of Psychophysical Theory). But empirical data prove otherwise and consistently reveal what Fechner (1860/1966, in Elements of Psychophysics) called time-order errors, whereby the magnitude of the stimulus presented in one of the intervals is systematically underestimated relative to the other. Here we discuss sensory factors (temporary desensitization) and procedural glitches (short interstimulus or intertrial intervals and response bias) that might explain the time-order error, and we derive a formal model indicating how these factors make observed performance vary with presentation order despite a single underlying mechanism. Experimental results are also presented illustrating the conventional failure of the balance condition and testing the hypothesis that time-order errors result from contamination by the factors included in the model.

Erro invalidante da dogmática do negócio jurídico

A regulamentação das hipóteses de erro no Direito Obrigacional foi objeto de profunda alteração em razão da nova redação atribuída à matéria pelo novo Código Civil e em razão do novo cenário desenhado pelo princípio da manutenção do contrato. A presente dissertação trata das diferenças entre a regulamentação do erro em face do Código anterior (1916 – “CC/16”, artigos 86 a 113) e do novo Código (2002 – “CC/02”, artigos 138 a 166). Além disso, a dissertação trata sobre as conseqüências advindas do desfazimento do negócio jurídico por erro, inclusive sobre eventual indenização. As questões propostas e que subjazem esta dissertação são: em quais situações a parte pode requerer o desfazimento por erro? A existência de erro, somente, é suficiente para que se declare inválido o contrato? E quais são as conseqüências da invalidação do negócio jurídico? Há algum dever indenizatório? As respostas a essas questões serão umas, se analisadas a partir das regras do Código Civil de 1916, e outras, se respondidas com base nas regras do Código Civil de 2002. A dissertação analisa o fato de, em regra, a doutrina apontar como modificação do novo Código Civil a introdução do princípio da proteção da confiança daquele que não agiu em erro. Na verdade, no entanto, essa proteção já era implementada na vigência do Código Civil anterior (CC/16), por meio do dever de indenizar. Portanto, a proteção da outra parte não é novidade introduzida pelo novo Código Civil (CC/02). A tese exposta nesta dissertação aponta para o fato de que, além da proteção da outra parte, a lei protege o contrato em si, como uma forma de proteger o comércio, ou seja, todos os demais contratos que dependem dele, direta ou indiretamente. E essa proteção é colocada em prática ao se dificultar o desfazimento do negócio jurídico por erro. Nesse sentido, o novo Código Civil inovou ao acrescentar um outro requisito para o desfazimento do negócio por erro: a sua recognoscibilidade.

Substance use and depression. Comparative course in adolescents.

OBJECTIVE: To examine the relation between depression and substance use in adolescents and the concomitant courses of both disorders. METHODS: Four individual interviews were administered to 85 adolescent substance users aged 14-19 years (mean 17.1 years, SD 1.4) over a 3.5 year period using the Adolescent Drug Abuse Interview (ADAD) and the Beck Depression Inventory (BDI-13). RESULTS: No predictive effect was observed on one dimension over the other, but each dimension was predictive of its own course. A decrease in substance-use severity paralleled a decrease in depressive state. Similarly, stable substance-use rates, either at a low or a high level, tended to be associated with low or high levels of depression, respectively. However, an increase in substance use was not accompanied by an increase in depressive states. Moreover, depression varied greatly between adolescents, and according to gender and age. CONCLUSIONS: Depressive states and substance use in adolescents can vary considerably overtime, and are closely but rather synchronically related. Since most of the adolescents do not seek help for substance-related problems, substance use should be systematically assessed in adolescents presenting with a depressive state.

Not in Education, Employment, or Training status among young Swiss men. Longitudinal associations with mental health and substance use.

PURPOSE: Not in Education, Employment, or Training (NEET) youth are youth disengaged from major social institutions and constitute a worrying concern. However, little is known about this subgroup of vulnerable youth. This study aimed to examine if NEET youth differ from other contemporaries in terms of personality, mental health, and substance use and to provide longitudinal examination of NEET status, testing its stability and prospective pathways with mental health and substance use. METHODS: As part of the Cohort Study on Substance Use Risk Factors, 4,758 young Swiss men in their early 20s answered questions concerning their current professional and educational status, personality, substance use, and symptomatology related to mental health. Descriptive statistics, generalized linear models for cross-sectional comparisons, and cross-lagged panel models for longitudinal associations were computed. RESULTS: NEET youth were 6.1% at baseline and 7.4% at follow-up with 1.4% being NEET at both time points. Comparisons between NEET and non-NEET youth showed significant differences in substance use and depressive symptoms only. Longitudinal associations showed that previous mental health, cannabis use, and daily smoking increased the likelihood of being NEET. Reverse causal paths were nonsignificant. CONCLUSIONS: NEET status seemed to be unlikely and transient among young Swiss men, associated with differences in mental health and substance use but not in personality. Causal paths presented NEET status as a consequence of mental health and substance use rather than a cause. Additionally, this study confirmed that cannabis use and daily smoking are public health problems. Prevention programs need to focus on these vulnerable youth to avoid them being disengaged.

Correcting Measurement Error Bias in Interaction Models with Small Samples

Several methods have been suggested to estimate non-linear models with interaction terms in the presence of measurement error. Structural equation models eliminate measurement error bias, but require large samples. Ordinary least squares regression on summated scales, regression on factor scores and partial least squares are appropriate for small samples but do not correct measurement error bias. Two stage least squares regression does correct measurement error bias but the results strongly depend on the instrumental variable choice. This article discusses the old disattenuated regression method as an alternative for correcting measurement error in small samples. The method is extended to the case of interaction terms and is illustrated on a model that examines the interaction effect of innovation and style of use of budgets on business performance. Alternative reliability estimates that can be used to disattenuate the estimates are discussed. A comparison is made with the alternative methods. Methods that do not correct for measurement error bias perform very similarly and considerably worse than disattenuated regression

A new estimator to minimize the error due to breathing in the measurement of respiratory impedance

This paper presents a new respiratory impedance estimator to minimize the error due to breathing. Its practical reliability was evaluated in a simulation using realistic signals. These signals were generated by superposing pressure and flow records obtained in two conditions: 1) when applying forced oscillation to a resistance- inertance- elastance (RIE) mechanical model; 2) when healthy subjects breathed through the unexcited forced oscillation generator. Impedances computed (4-32 Hz) from the simulated signals with the new estimator resulted in a mean value which was scarcely biased by the added breathing (errors less than 1 percent in the mean R, I , and E ) and had a small variability (coefficients of variation of R, I, and E of 1.3, 3.5, and 9.6 percent, respectively). Our results suggest that the proposed estimator reduces the error in measurement of respiratory impedance without appreciable extracomputational cost.

Psychiatric and neurological symptoms in schizophrenia and substance use disorder patients treated for 12-weeks with quetiapine

Contexte Autant dans une population schizophrène que non schizophrène, l‘abus de substance a pour conséquence la manifestation de symptômes psychiatriques et neurologiques. Dans les présentes études cas-témoins, nous avons examiné les différences initiales ainsi que les changements suite au traitement de 12 semaines à la quetiapine au niveau de la sévérité de la toxicomanie et des symptômes psychiatriques et neurologiques chez 3 groupes distincts. Ces 3 groupes sont: des patients schizophrènes avec une toxicomanie (double diagnostic: DD), des patients schizophrènes sans toxicomanie concomittante (SCZ) et finalement, des toxicomanes non schizophrènes (SUD). Parallèlement, afin de nous aider à interpréter nos résultats, nous avons mené deux revues systématiques: la première regardait l‘effet d‘antipsychotiques dans le traitement de troubles d‘abus/dépendance chez des personnes atteintes ou non de psychoses, la deuxième comparait l‘efficacité de la quetiapine et sa relation dose-réponse parmi différents désordres psychiatriques. Méthodes Pour nos études cas-témoins, l‘ensemble des symptômes psychiatriques et neurologiques ont été évalués via l‘Échelle du syndrome positif et négatif (PANSS), l‘Échelle de dépression de Calgary, l‘Échelle des symptômes extrapyramidaux (ESRS) ainsi qu‘avec l‘Échelle d‘akathisie de Barnes. Résultats À la suite du traitement de 12 semaines avec la quetiapine, les groupes SCZ et DD recevaient des doses de quetiapine significativement plus élevées (moyenne = 554 et 478 mg par jour, respectivement) par rapport au groupe SUD (moyenne = 150 mg par jour). Aussi, nous avons observé chez ces mêmes patients SUD une plus importante baisse du montant d‘argent dépensé par semaine en alcool et autres drogues, ainsi qu‘une nette amélioration de la sévérité de la toxicomanie comparativement aux patients DD. Par conséquent, à la fin de l‘essai de 12 semaines, il n‘y avait pas de différence significative dans l‘argent dépensé en alcool et drogues entre les deux groupes de toxicomanes iv or, les patients DD présentait, comme au point de départ, un score de toxicomanie plus sévère que les SUD. Étonnamment, aux points initial et final de l‘étude, le groupe DD souffrait de plus de symptômes parkinsoniens et de dépression que le groupe SCZ. Par ailleurs, nous avons trouvé qu‘initiallement, les patients SUD présentaient significativement plus d‘akathisie, mais qu‘en cours de traitement, cette akathisie reliée à l‘abus/dépendance de cannabis s‘est nettement améliorée en comparaison aux patients SCZ. Enfin, les patients SUD ont bénéficié d‘une plus grande diminution de leurs symptômes positifs que les 2 groupes atteints de schizophrénie. Conclusions Bref, l‘ensemble de nos résultats fait montre d‘une vulnérabilité accentuée par les effets négatifs de l‘alcool et autres drogues dans une population de patients schizophrènes. Également, ces résultats suggèrent que l‘abus de substance en combinaison avec les états de manque miment certains symptômes retrouvés en schizophrénie. De futures études seront nécessaires afin de déterminer le rôle spécifique qu‘a joué la quetiapine dans ces améliorations.

Model Diagnostics in the presence of measurement error

The problem of using information available from one variable X to make inferenceabout another Y is classical in many physical and social sciences. In statistics this isoften done via regression analysis where mean response is used to model the data. Onestipulates the model Y = µ(X) +ɛ. Here µ(X) is the mean response at the predictor variable value X = x, and ɛ = Y - µ(X) is the error. In classical regression analysis, both (X; Y ) are observable and one then proceeds to make inference about the mean response function µ(X). In practice there are numerous examples where X is not available, but a variable Z is observed which provides an estimate of X. As an example, consider the herbicidestudy of Rudemo, et al. [3] in which a nominal measured amount Z of herbicide was applied to a plant but the actual amount absorbed by the plant X is unobservable. As another example, from Wang [5], an epidemiologist studies the severity of a lung disease, Y , among the residents in a city in relation to the amount of certain air pollutants. The amount of the air pollutants Z can be measured at certain observation stations in the city, but the actual exposure of the residents to the pollutants, X, is unobservable and may vary randomly from the Z-values. In both cases X = Z+error: This is the so called Berkson measurement error model.In more classical measurement error model one observes an unbiased estimator W of X and stipulates the relation W = X + error: An example of this model occurs when assessing effect of nutrition X on a disease. Measuring nutrition intake precisely within 24 hours is almost impossible. There are many similar examples in agricultural or medical studies, see e.g., Carroll, Ruppert and Stefanski [1] and Fuller [2], , among others. In this talk we shall address the question of fitting a parametric model to the re-gression function µ(X) in the Berkson measurement error model: Y = µ(X) + ɛ; X = Z + η; where η and ɛ are random errors with E(ɛ) = 0, X and η are d-dimensional, and Z is the observable d-dimensional r.v.

Correcting Measurement Error Bias in Interaction Models with Small Samples

Several methods have been suggested to estimate non-linear models with interaction terms in the presence of measurement error. Structural equation models eliminate measurement error bias, but require large samples. Ordinary least squares regression on summated scales, regression on factor scores and partial least squares are appropriate for small samples but do not correct measurement error bias. Two stage least squares regression does correct measurement error bias but the results strongly depend on the instrumental variable choice. This article discusses the old disattenuated regression method as an alternative for correcting measurement error in small samples. The method is extended to the case of interaction terms and is illustrated on a model that examines the interaction effect of innovation and style of use of budgets on business performance. Alternative reliability estimates that can be used to disattenuate the estimates are discussed. A comparison is made with the alternative methods. Methods that do not correct for measurement error bias perform very similarly and considerably worse than disattenuated regression

Convergence Property of the Measurement Gross Error Correction in Power System State Estimation, Using Geometrical Background

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Variability in the prevalence of adult ADHD in treatment seeking substance use disorder patients: results from an international multi-center study exploring DSM-IV and DSM-5 criteria

Background: Available studies vary in their estimated prevalence of attention deficit/hyperactivity disor-der (ADHD) in substance use disorder (SUD) patients, ranging from 2 to 83%. A better understanding ofthe possible reasons for this variability and the effect of the change from DSM-IV to DSM-5 is needed.Methods: A two stage international multi-center, cross-sectional study in 10 countries, among patientsform inpatient and outpatient addiction treatment centers for alcohol and/or drug use disorder patients. Atotal of 3558 treatment seeking SUD patients were screened for adult ADHD. A subsample of 1276 subjects,both screen positive and screen negative patients, participated in a structured diagnostic interview. 5AdultsResults: Prevalence of DSM-IV and DSM-5 adult ADHD varied for DSM-IV from 5.4% (CI 95%: 2.4–8.3) forHungary to 31.3% (CI 95%:25.2–37.5) for Norway and for DSM-5 from 7.6% (CI 95%: 4.1–11.1) for Hungary to32.6% (CI 95%: 26.4–38.8) for Norway. Using the same assessment procedures in all countries and centersresulted in substantial reduction of the variability in the prevalence of adult ADHD reported in previousstudies among SUD patients (2–83% → 5.4–31.3%). The remaining variability was partly explained byprimary substance of abuse and by country (Nordic versus non-Nordic countries). Prevalence estimatesfor DSM-5 were slightly higher than for DSM-IV.Conclusions: Given the generally high prevalence of adult ADHD, all treatment seeking SUD patientsshould be screened and, after a confirmed diagnosis, treated for ADHD since the literature indicates poorprognoses of SUD in treatment seeking SUD patients with ADHD.

Psychiatric comorbidity in treatment-seeking substance use disorder patients with and without attention deficit hyperactivity disorder: results of the IASP study

Aims To determine comorbidity patterns in treatment-seeking substance use disorder (SUD) patients with and without adult attention deficit hyperactivity disorder (ADHD), with an emphasis on subgroups defined by ADHD subtype, taking into account differences related to gender and primary substance of abuse. Design Data were obtained from the cross-sectional International ADHD in Substance use disorder Prevalence (IASP) study. Setting Forty-seven centres of SUD treatment in 10 countries. Participants A total of 1205 treatment-seeking SUD patients. Measurements Structured diagnostic assessments were used for all disorders: presence of ADHD was assessed with the Conners' Adult ADHD Diagnostic Interview for DSM-IV (CAADID), the presence of antisocial personality disorder (ASPD), major depression (MD) and (hypo)manic episode (HME) was assessed with the Mini International Neuropsychiatric Interview-Plus (MINI Plus), and the presence of borderline personality disorder (BPD) was assessed with the Structured Clinical Interview for DSM-IV Axis II (SCID II). Findings The prevalence of DSM-IV adult ADHD in this SUD sample was 13.9%. ASPD [odds ratio (OR) = 2.8, 95% confidence interval (CI) = 1.8–4.2], BPD (OR = 7.0, 95% CI = 3.1–15.6 for alcohol; OR = 3.4, 95% CI = 1.8–6.4 for drugs), MD in patients with alcohol as primary substance of abuse (OR = 4.1, 95% CI = 2.1–7.8) and HME (OR = 4.3, 95% CI = 2.1–8.7) were all more prevalent in ADHD+ compared with ADHD− patients (P < 0.001). These results also indicate increased levels of BPD and MD for alcohol compared with drugs as primary substance of abuse. Comorbidity patterns differed between ADHD subtypes with increased MD in the inattentive and combined subtype (P < 0.01), increased HME and ASPD in the hyperactive/impulsive (P < 0.01) and combined subtypes (P < 0.001) and increased BPD in all subtypes (P < 0.001) compared with SUD patients without ADHD. Seventy-five per cent of ADHD patients had at least one additional comorbid disorder compared with 37% of SUD patients without ADHD. Conclusions Treatment-seeking substance use disorder patients with attention deficit hyperactivity disorder are at a very high risk for additional externalizing disorders.

Evaluation of risk factors for long term changes in refractive error among adult patients at a Dallas Texas private setting A retrospective chart-review study

Background. Over 39.9% of the adult population forty or older in the United States has refractive error, little is known about the etiology of this condition and associated risk factors and their entailed mechanism due to the paucity of data regarding the changes of refractive error for the adult population over time.^ Aim. To evaluate risk factors over a long term, 5-year period, in refractive error changes among persons 43 or older by testing the hypothesis that age, gender, systemic diseases, nuclear sclerosis and baseline refractive errors are all significantly associated with refractive errors changes in patients at a Dallas, Texas private optometric office.^ Methods. A retrospective chart review of subjective refraction, eye health, and self-report health history was done on patients at a private optometric office who were 43 or older in 2000 who had eye examinations both in 2000 and 2005. Aphakic and pseudophakic eyes were excluded as well as eyes with best corrected Snellen visual acuity of 20/40 and worse. After exclusions, refraction was obtained on 114 right eyes and 114 left eyes. Spherical equivalent (sum of sphere + ½ cylinder) was used as the measure of refractive error.^ Results. Similar changes in refractive error were observed for the two eyes. The 5-year change in spherical power was in a hyperopic direction for younger age groups and in a myopic direction for older subjects, P<0.0001. The gender-adjusted mean change in refractive error in right eyes of persons aged 43 to 54, 55 to 64, 65 to 74, and 75 or older at baseline was +0.43D, +0.46 D, -0.09 D, and -0.23D, respectively. Refractive change was strongly related to baseline nuclear cataract severity; grades 4 to 5 were associated with a myopic shift (-0.38 D, P< 0.0001). The mean age-adjusted change in refraction was +0.27 D for hyperopic eyes, +0.56 D for emmetropic eyes, and +0.26 D for myopic eyes.^ Conclusions. This report has documented refractive error changes in an older population and confirmed reported trends of a hyperopic shift before age 65 and a myopic shift thereafter associated with the development of nuclear cataract.^

Slope estimation in a parametric measurement error model: A simulation study

In regression analysis, covariate measurement error occurs in many applications. The error-prone covariates are often referred to as latent variables. In this proposed study, we extended the study of Chan et al. (2008) on recovering latent slope in a simple regression model to that in a multiple regression model. We presented an approach that applied the Monte Carlo method in the Bayesian framework to the parametric regression model with the measurement error in an explanatory variable. The proposed estimator applied the conditional expectation of latent slope given the observed outcome and surrogate variables in the multiple regression models. A simulation study was presented showing that the method produces estimator that is efficient in the multiple regression model, especially when the measurement error variance of surrogate variable is large.^