Translation and validation of the Spanish version of the Chronic Illness Anticipated Stigma Scale (CIASS) in Colombian patients diagnosed with chronic illnesses

Objective: Determine the psychometric properties of the CIASS scale for Colombian patients living with chronic diseases. Method: A Spanish version of the scale was distributed to a sample of 230 patients (33.2% male, aged 18–98 years) diagnosed with chronic diseases. A confirmatory factor analysis was performed using unweighted least squares to determine the scale’s structural validity, Cronbach’s alpha was calculated to determine the scale’s reliability, and correlations with related constructs were calculated to determine the scale’s convergent validity. Results: Confirmatory factor analysis suggested that the factor structure of the scale was a satisfactory fit to the proposed theoretical model (χ2 = 3133.26, df = 526, root mean square error of approximation [RMSEA] = 0.082, P-Value = 0.00, CFI = 1.00, root mean square residual [RMR] = 0.11). The internal consistency of the scale was strong (Cronbach’s α = .815), indicating that the scale was reliable. We found that the discrimination index of CIASS scale items were high (r =  .647–.870). Convergent validity was also supported, associations observed with lower coping and greater negative emotion scores. Conclusion: The CIASS scale is a valid and reliable instrument for the assessment of anticipated stigma in Colombian patients with chronic illnesses

A Simple Monte Carlo Framework to Assess Suicide Risk in Adolescents: A Study at a High School in Colombia

It is very common to perform statistical tests to obtain insights about populations based on samples. For instance, in the context of psychology, when a set of instruments are applied to individuals, psychologists typically look for an explanation of particular psychological constructs (variables), such as personality, intelligence, or emotional functioning. It is common to cross statistical information from the results of different psychological tests to measure certain variables or to confirm prior beliefs. Here, we estimate the Joint Probability Density Function of suicide-related vulnerability and protective factors to assess suicide risk in adolescents. A Markov Chain Monte Carlo Method is employed to move away from the typical Gaussian assumption on data. This allows us to estimate probabilities of the development of suicidal ideation based on samples (which form a Markov chain). We employ our proposed statistical method at a high school in Colombia. The results reveal that adolescents can develop suicidal ideation as a consequence of the following factors, together with their corresponding probabilities: poor school performance 52%, low academic expectations 27%, school integration problems 68%, risky eating behaviors (binge-purge) 42%, risky eating behaviors (compensatory measurements) 21%, risky eating habits (restriction) 22%, and low family functionality 16%

Reproducibility of fluorescent expression from engineered biological constructs in E. coli

We present results of the first large-scale interlaboratory study carried out in synthetic biology, as part of the 2014 and 2015 International Genetically Engineered Machine (iGEM) competitions. Participants at 88 institutions around the world measured fluorescence from three engineered constitutive constructs in E. coli. Few participants were able to measure absolute fluorescence, so data was analyzed in terms of ratios. Precision was strongly related to fluorescent strength, ranging from 1.54-fold standard deviation for the ratio between strong promoters to 5.75-fold for the ratio between the strongest and weakest promoter, and while host strain did not affect expression ratios, choice of instrument did. This result shows that high quantitative precision and reproducibility of results is possible, while at the same time indicating areas needing improved laboratory practices.Peer reviewe