In self-report surveys, it is common that some individuals do not pay enough attention and effort to give valid responses. Our aim was to investigate the extent to which careless and insufficient effort responding contributes to the biasing of data. We performed analyses of dimensionality, internal structure, and data reliability of four personality scales (extroversion, conscientiousness, stability, and dispositional optimism) in two independent samples. In order to identify careless/insufficient effort (C/IE) respondents, we used a factor mixture model (FMM) designed to detect inconsistencies of response to items with different semantic polarity. The FMM identified between 4.4% and 10% of C/IE cases, depending on the scale and the sample examined. In the complete samples, all the theoretical models obtained an unacceptable fit, forcing the rejection of the starting hypothesis and making additional wording factors necessary. In the clean samples, all the theoretical models fitted satisfactorily, and the wording factors practically disappeared. Trait estimates in the clean samples were between 4.5% and 11.8% more accurate than in the complete samples. These results show that a limited amount of C/IE data can lead to a drastic deterioration in the fit of the theoretical model, produce large amounts of spurious variance, raise serious doubts about the dimensionality and internal structure of the data, and reduce the reliability with which the trait scores of all surveyed are estimated. Identifying and filtering C/IE responses is necessary to ensure the validity of research results.

Quality of life, Quality of life models, Structural equation modeling, Validity, Social service recipients,

We tested first-order factor and bifactor models of attention-deficit/hyperactivity disorder (ADHD) using confirmatory factor analysis (CFA) and exploratory structural equation modeling (ESEM) to adequately summarize the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition, (DSM-IV-TR) symptoms observed in a Spanish sample of preschoolers and kindergarteners. Six ESEM and CFA models were estimated based on teacher evaluations of the behavior of 638 children 4 to 6 years of age. An ESEM bifactor model with a central dimension plus 3 specific factors (inattention, hyperactivity, and impulsivity) showed the best fit and interpretability. Strict invariance between the sexes was observed. The bifactor model provided a solution to previously encountered inconsistencies in the factorial models of ADHD in young children. However, the low reliability of the specific factors casts doubt on the utility of the subscales for ADHD measurement. More research is necessary to clarify the nature of G and S factors of ADHD.

This paper presents the psychometric properties of a new measure of social anxiety, the Social Anxiety Questionnaire for adults (SAQ), composed of 30 items that were developed based on participants from 16 Latin American countries, Spain, and Portugal. Two groups of participants were included in the study: a non-clinical group involving 18,133 persons and a clinical group comprising 334 patients with a diagnosis of social anxiety disorder (social phobia). Exploratory and confirmatory factor analyses supported a 5-factor structure of the questionnaire. The factors were labeled: 1) Interactions with strangers, 2) Speaking in public/talking with people in authority, 3) Interactions with the opposite sex, 4) Criticism and embarrassment, and 5) Assertive expression of annoyance, disgust or displeasure. Psychometric evidence supported the internal consistency, convergent validity, and measurement invariance of the SAQ. To facilitate clinical applications, a ROC analysis identified cut scores for men and women for each factor and for the global score.

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