Methods for questionnaire design: a taxonomy linking procedures to test goals.

BACKGROUND: In the clinical field, the use of questionnaires is ubiquitous, and many different methods for constructing them are available. The reason for using a specific method is usually lacking, and a generally accepted classification of methods is not yet available. To guide test developers and users, this article presents a taxonomy for methods of questionnaire design which links the methods to the goal of a test. METHODS: The taxonomy assumes that construction methods are directed towards psychometric aspects. Four stages of test construction are distinguished to describe methods: concept analysis, item production, scale construction, and evaluation; the scale construction stage is used for identifying methods. It distinguishes six different methods: the rational method utilizes expert judgments to ensure face validity. The prototypical method uses prototypicality judgments to ensure process validity. In the internal method, item sets are selected that optimize homogeneity. The external method optimizes criterion validity by selecting items that best predict an external criterion. Under the construct method theoretical considerations are used to optimize construct validity. The facet method is aimed at optimizing content validity through a complete representation of the concept domain. CONCLUSION: The taxonomy is comprehensive, constitutes a useful tool for describing procedures used in questionnaire design, and allows for setting up a test construction plan in which the priorities among psychometric aspects are made explicit.

Six factors of adult dyslexia assessed by cognitive tests and self-report questions: Very high predictive validity.

The Multiple Diagnostic Digital Dyslexia Test for Adults (MDDDT-A) consists of 12 newly developed tests and self-report questions in the Dutch language. Predictive validity and construct validity were investigated and compared with validity of a standard test battery of dyslexia (STB) in a sample of 154 students. There are three main results. First, various analyses of principal components showed that six or more factors of dyslexia can be distinguished (rapid naming, spelling, reading, short-term memory, confusion, phonology, attention, complexity). All factors are represented by the MDDDT-A. Second, various discriminant analyses showed good predictive validity for both the tests of the MDDDT-A (90%) and the STB (90%). However, predictive validity of the questionnaire was highest (97%). Third, we analysed the best predictors of dyslexia and found that predictive validity is higher when construct validity is high, that is when a set of predictors represents many characteristics of dyslexia. The main conclusion is that a digital test battery can be a reliable screening instrument for dyslexia in students, especially when it is accompanied by self-report questions. A theoretical conclusion is that dyslexia is characterized by at least six cognitive impairments in a complex way. In students, this structure may be modulated by high intelligence and good schooling through various compensation strategies. It is therefore recommended to include assessments of all characteristics of dyslexia to achieve the most reliable diagnoses in different samples and in different countries.

Five Describing Factors of Dyslexia.

Two subtypes of dyslexia (phonological, visual) have been under debate in various studies. However, the number of symptoms of dyslexia described in the literature exceeds the number of subtypes, and underlying relations remain unclear. We investigated underlying cognitive features of dyslexia with exploratory and confirmatory factor analyses. A sample of 446 students (63 with dyslexia) completed a large test battery and a large questionnaire. Five factors were found in both the test battery and the questionnaire. These 10 factors loaded on 5 latent factors (spelling, phonology, short-term memory, rhyme/confusion, and whole-word processing/complexity), which explained 60% of total variance. Three analyses supported the validity of these factors. A confirmatory factor analysis fit with a solution of five factors (RMSEA = .03). Those with dyslexia differed from those without dyslexia on all factors. A combination of five factors provided reliable predictions of dyslexia and nondyslexia (accuracy >90%). We also looked for factorial deficits on an individual level to construct subtypes of dyslexia, but found varying profiles. We concluded that a multiple cognitive deficit model of dyslexia is supported, whereas the existence of subtypes remains unclear. We discussed the results in relation to advanced compensation strategies of students, measures of intelligence, and various correlations within groups of those with and without dyslexia.

Dyslexia and voxel-based morphometry: correlations between five behavioural measures of dyslexia and gray and white matter volumes.

In voxel-based morphometry studies of dyslexia, the relation between causal theories of dyslexia and gray matter (GM) and white matter (WM) volume alterations is still under debate. Some alterations are consistently reported, but others failed to reach significance. We investigated GM alterations in a large sample of Dutch students (37 dyslexics and 57 non-dyslexics) with two analyses: group differences in local GM and total GM and WM volume and correlations between GM and WM volumes and five behavioural measures. We found no significant group differences after corrections for multiple comparisons although total WM volume was lower in the group of dyslexics when age was partialled out. We presented an overview of uncorrected clusters of voxels (p < 0.05, cluster size k > 200) with reduced or increased GM volume. We found four significant correlations between factors of dyslexia representing various behavioural measures and the clusters found in the first analysis. In the whole sample, a factor related to performances in spelling correlated negatively with GM volume in the left posterior cerebellum. Within the group of dyslexics, a factor related to performances in Dutch-English rhyme words correlated positively with GM volume in the left and right caudate nucleus and negatively with increased total WM volume. Most of our findings were in accordance with previous reports. A relatively new finding was the involvement of the caudate nucleus. We confirmed the multiple cognitive nature of dyslexia and suggested that experience greatly influences anatomical alterations depending on various subtypes of dyslexia, especially in a student sample.

A new self-report inventory of dyslexia for students: criterion and construct validity.

The validity of a Dutch self-report inventory of dyslexia was ascertained in two samples of students. Six biographical questions, 20 general language statements and 56 specific language statements were based on dyslexia as a multi-dimensional deficit. Dyslexia and non-dyslexia were assessed with two criteria: identification with test results (Sample 1) and classification using biographical information (both samples). Using discriminant analyses, these criteria were predicted with various groups of statements. All together, 11 discriminant functions were used to estimate classification accuracy of the inventory. In Sample 1, 15 statements predicted the test criterion with classification accuracy of 98%, and 18 statements predicted the biographical criterion with classification accuracy of 97%. In Sample 2, 16 statements predicted the biographical criterion with classification accuracy of 94%. Estimations of positive and negative predictive value were 89% and 99%. Items of various discriminant functions were factor analysed to find characteristic difficulties of students with dyslexia, resulting in a five-factor structure in Sample 1 and a four-factor structure in Sample 2. Answer bias was investigated with measures of internal consistency reliability. Less than 20 self-report items are sufficient to accurately classify students with and without dyslexia. This supports the usefulness of self-assessment of dyslexia as a valid alternative to diagnostic test batteries.

Identifying dyslexia in adults: an iterative method using the predictive value of item scores and self-report questions.

Methods for identifying dyslexia in adults vary widely between studies. Researchers have to decide how many tests to use, which tests are considered to be the most reliable, and how to determine cut-off scores. The aim of this study was to develop an objective and powerful method for diagnosing dyslexia. We took various methodological measures, most of which are new compared to previous methods. We used a large sample of Dutch first-year psychology students, we considered several options for exclusion and inclusion criteria, we collected as many cognitive tests as possible, we used six independent sources of biographical information for a criterion of dyslexia, we compared the predictive power of discriminant analyses and logistic regression analyses, we used both sum scores and item scores as predictor variables, we used self-report questions as predictor variables, and we retested the reliability of predictions with repeated prediction analyses using an adjusted criterion. We were able to identify 74 dyslexic and 369 non-dyslexic students. For 37 students, various predictions were too inconsistent for a final classification. The most reliable predictions were acquired with item scores and self-report questions. The main conclusion is that it is possible to identify dyslexia with a high reliability, although the exact nature of dyslexia is still unknown. We therefore believe that this study yielded valuable information for future methods of identifying dyslexia in Dutch as well as in other languages, and that this would be beneficial for comparing studies across countries.

Cohort differences in Big Five personality factors over a period of 25 years.

The notion of personality traits implies a certain degree of stability in the life span of an individual. But what about generational effects? Are there generational changes in the distribution or structure of personality traits? This article examines cohort changes on the Big Five personality factors Extraversion, Agreeableness, Conscientiousness, Neuroticism, and Openness to Experience, among first-year psychology students in The Netherlands, ages 18 to 25 years, between 1982 and 2007. Because measurement invariance of a personality test is essential for a sound interpretation of cohort differences in personality, we first assessed measurement invariance with respect to cohort for males and females separately on the Big Five personality factors, as measured by the Dutch instrument Five Personality Factors Test. Results identified 11 (females) and 2 (males) biased items with respect to cohort, out of a total of 70 items. Analyzing the unbiased items, results indicated small linear increases over time in Extraversion, Agreeableness, and Conscientiousness and small linear decreases over time in Neuroticism. No clear patterns were found on the Openness to Experience factor. Secondary analyses on students from 1971 to 2007 of females and males of different ages together revealed linear trends comparable to those in the main analyses among young adults between 1982 onward. The results imply that the broad sociocultural context may affect personality factors.

The cognitive and affective alexithymia dimensions in the regulation of sympathetic responses.

OBJECTIVE: The literature regarding research into alexithymia and sympathetic responses is far from consistent. An explanation might be on the way subjects are classified. Generally, subjects are diagnosed as either alexithymic or non-alexithymic on the basis of questionnaires focusing on the cognitive aspects of alexithymia. However, alexithymia, as originally defined, concerns both emotion-affective and emotion-cognitive deficits. The aim of the present paper is to study the importance of the affective and cognitive alexithymia components in the regulation of sympathetic responses. METHODS: Subjects, who scored extremely (either high or low) on both the cognitive and the affective components of alexithymia, were shown neutral and emotional pictures, while their GSR was measured. RESULTS: The affective alexithymia component, not the cognitive component, turned out to be an important factor in the regulation of GSR peak amplitude. The results further indicate a significant interaction of type of emotional deficit (cognitive by affective) on GSR latency times. Finally, suggestive evidence indicated that baselines values, defined by the levels during the second preceding the stimulus, are related to the cognitive component of alexithymia, in the sense that higher emotion-cognitive capacities result in higher baseline values. CONCLUSIONS: We cautiously conclude that the classification of alexithymics on the basis of both the affective and cognitive components, rather than on the basis of the cognitive component only, might provide more consistent research results, and thus lead to a better understanding of emotional physiological responses in alexithymic subjects.

Cognitive neuropsychology of alexithymia: implications for personality typology.

INTRODUCTION: We examine the cognitive neuroscience of the five components of the alexithymia syndrome, and propose a classification of alexithymia types based on psychobiological traits. METHOD: Literature review. RESULTS: The following neural structures have been shown to be prominent in emotional function: right and left hemisphere, corpus callosum, anterior commissure, anterior cingulate, prefrontal cortex, amygdala, and insular cortex. The specific relevance of these structures to alexithymia is discussed. CONCLUSIONS: The following conclusions and/or propositions are presented: The right hemisphere produces a global, nonverbal overview of emotional information; the left hemisphere seems dedicated to analysing emotions and higher explicit emotional cognitions. Both orbitoprefrontal cortices are important in affective aspects of alexithymia, while right temporal cortex is involved in cognitive aspects. Two subparts of anterior cingulate fulfil functions in the affective and cognitive dimensions of alexithymia. The amygdalae are involved in both cognitive and affective aspects. All structures mentioned can modulate one another. The role of interhemispheric information transfer via the corpus callosum and the anterior commissure is also discussed. The evidence that that cognitive processing of emotional information inhibits affective processing of such information is discussed in terms of its implications for a theory of alexithymia subtypes.