ABSTRACT
BACKGROUND: In the past decade, the bifactor model of attention-deficit/hyperactivity disorder (ADHD) has been extensively researched. This model consists of an ADHD general dimension and two specific factors: inattention and hyperactivity/impulsivity. All studies conclude that the bifactor is superior to the traditional two-correlated factors model, according to the fit obtained by factor analysis. However, the proper interpretation of a bifactor not only depends on the fit but also on the quality of the measurement model. OBJECTIVE: To evaluate the model-based reliability, distribution of common variance and construct replicability of general and specific ADHD factors. METHOD: We estimated expected common variance, omega hierarchical/subscale and H-index from standardized factor loadings of 31 ADHD bifactor models previously published. RESULTS AND CONCLUSION: The ADHD general factor explained most of the common variance. Given the low reliable variance ratios, the specific factors were difficult to interpret. However, in clinical samples, inattention acquired sufficient specificity and stability for interpretation beyond the general factor. Implications for research and clinical practice are discussed.
Subject(s)
Attention Deficit Disorder with Hyperactivity/psychology , Models, Psychological , Factor Analysis, Statistical , Humans , Psychometrics , Reproducibility of ResultsABSTRACT
The learned predictiveness effect or LPE is the finding that when people learn that certain cues are reliable predictors of an outcome in an initial stage of training (phase 1), they exhibit a learning bias in favor of these cues in a subsequent training involving new outcomes (phase 2) despite all cues being equally reliable in phase 2. In Experiment 1, we replicate the basic effect and found that the addition of a secondary memory task during phase 2 had no reliable influence on the LPE. In Experiment 2, we demonstrated that the same secondary task can either facilitate or disrupt the LPE, depending on whether the outcomes of phase 1 were affectively congruent or incongruent with the outcomes of phase 2. These findings are discussed in relationship to associative and inferential accounts of LPE (AU)
El efecto de la predictibilidad aprendida o LPE, es el hallazgo de que cuando las personas aprenden que algunos estímulos son predictores fiables de una consecuencia en una primera etapa del entrenamiento (fase 1), muestran un sesgo de aprendizaje a favor de éstos estímulos en un entrenamiento posterior que implica nuevas consecuencias (fase 2), a pesar de que todos los estímulos son igualmente fiables en la fase 2. En el Experimento 1, replicamos el efecto básico y demostramos que la ejecución de una tarea de memoria secundaria durante la fase 2 no tuvo una influencia significativa sobre la LPE. En el Experimento 2, demostramos que la misma tarea secundaria puede facilitar o interrumpir la LPE, dependiendo de si las consecuencias de la fase 1 fueron congruentes o incongruentes afectivamente con las consecuencias de la fase 2. Estos hallazgos son discutidos en relación a las explicaciones asociativa e inferencial de la LPE (AU)
Subject(s)
Humans , Cognitive Behavioral Therapy/methods , Cognitive Science/methods , Psychology, Experimental/methods , Psychology, Experimental/trends , Association Learning/physiology , Psychological Tests , Learning/physiology , Probability Learning , Analysis of Variance , Students/psychology , Education/methodsABSTRACT
The Diagnostic and Statistical Manual of Mental Disorders (DSM) diagnostic criteria assume that the 18 symptoms carry the same weight in an Attention Deficit with Hyperactivity Disorder (ADHD) diagnosis and bear the same discriminatory capacity. However, it is reasonable to think that symptoms may differ in terms of severity and even in the reliability with they represent the disorder. To test this hypothesis, the aim of this study was to calibrate in a sample of Spanish children (age 4-7; n = 784) a scale for assessing the symptoms of ADHD proposed by Diagnostic and Statistical Manual of Mental Disorders, IV-TR within the framework of Item Response Theory. Samejima's Graded Response Model was used as a method for estimating the item difficulty and discrimination parameters. The results showed that ADHD subscales (Attention Deficit and Hyperactivity / Impulsivity) had good psychometric properties and had also a good fit to the model. However, relevant differences between symptoms were observed at the level of severity, informativeness and reliability for the assessment of ADHD. This finding suggests that it would be useful to identify the symptoms that are more important than the others with regard to diagnosing ADHD.
