Psychometric evaluation and normative data for a Swedish version of the Patient Health Questionnaire 15‐Item Somatic Symptom Severity Scale

The lack of an available Swedish version of the Patient Health Questionnaire 15‐Item Somatic Symptom Severity Scale (PHQ‐15) motivated the present psychometric evaluation of such a version as well as providing normative data for the PHQ‐15. Data from 3,406 individuals who took part in the Västerbotten Environmental Health Study in Sweden were used. The respondents constitute a random sample, aged 18 to 79 years, stratified for age and sex. They responded to a Swedish translation of the PHQ‐15 as well as the Hospital Anxiety and Depression Scale, the Perceived Stress Scale, and the Shirom Melamed Burnout Questionnaire for assessment of convergent validity. The distribution of PHQ‐15 scores was positively skewed and mesokurtic in shape, and the internal consistency of the PHQ‐15 was satisfactory. Correlation coefficients between PHQ‐15 score and the measures of anxiety, depression, stress and mental/physical exhaustion indicate satisfactory validity. Normative data for PHQ‐15 scores as well as for categories of somatic symptom severity are provided. The favorable psychometric properties of the Swedish version of the PHQ‐15 suggest use of this instrument for quantification of somatization in Swedish and similar populations, and has the advantage of available normative data.     

Interpreting cross-sectional data on stages of change

Abstract

The vast majority of studies investigating stage theories of health behaviour such as the transtheoretical model have used a cross-sectional research design. Participants are classified into stages and compared on theoretically relevant variables. This paper discusses the proper interpretation of cross-sectional data on stages of change. Linear patterns are not consistent with the stage model assumption that different causal factors are important at different stages but discontinuity patterns (patterns that do not show consistent increments or decrements across stages) can be diagnostic of a stage model. Researchers who use cross-sectional designs should specify predictions concerning the patterns to be expected under a stage model and under possible rival models, and interpret their data accordingly. Wherever possible, they should conduct prospective longitudinal and experimental studies which enable stronger inferences to be drawn.     

Why and how we should care about the General Data Protection Regulation

Abstract

The General Data Protection Regulation (GDPR) is the new European Union-wide (EU) law on data protection, which is a great step towards more comprehensive and more far-reaching protection of individuals' personal data. In this editorial, we describe why and how we – as researchers within the field of health psychology – should care about the GDPR. In the first part, we explain when the GDPR is applicable, who is accountable for data protection, and what is covered by the notions of personal data and processing. In the second part, we explain aspects of the GDPR that are relevant for researchers within the field of health psychology (e.g., obtaining informed consent, data minimisation, and open science). We focus on questions that researchers may ask themselves in their daily practice. Compliance with the GDPR requires adopting research practices (e.g., data minimisation and anonymization procedures) that are not yet commonly used, but serve the fundamental right to protection of personal data of study participants.     

A normative study of the Children’s Color Trails Test (CCTT) in the Cypriot population

Background: The Children’s Color Trails Test (CCTT) is a neuropsychological test that measures attention, divided attention, and speed of mental processing. It has been increasingly used in the assessment of children in cross-cultural environments for neurological and psychiatric disorders such as seizures and closed head injuries, learning and/or language disabilities, attention deficit/hyperactivity disorder, children with manganese exposure, and children diagnosed with HIV virus. However, there is a paucity of studies presenting normative data. The aim of the present study was to provide normative data for the CCTT in the Cypriot population. Methods: A total of 709 native Cypriot children aged 7–16 years, recruited from various public schools across the island, took part in the study. Exclusion criteria involved the existence of neurological, psychiatric, cardiological, and metabolic diseases, premature birth, history of maternal alcohol and drug abuse during pregnancy, low birth weight, hearing loss, visual problems, native language other than Greek, and abnormality in fine-motor movements. Results: Age and gender were found to be important factors for the interpretation of scores in all CCTT variables. Older children required less time and exhibited fewer errors, near misses, and prompts compared to younger children. There was a consistent pattern of a 3–4 seconds improvement (less time in seconds) in the CCTT completion time as age increased. Conclusions: CCTT is a promising tool for the measurement of attention in the native Cypriot population. Further research is needed in children diagnosed with various neurological and psychiatric diseases in order to estimate validity of the CCTT in clinical populations.     

Feature importance in feature generation and typicality rating

Many theoretical models of cognition are based on the assumption that cognitive processes and representations are hierarchically structured. The issue of whether these hierarchies are mere constructs or conceptual tools, or whether they have psychological and neurological reality, is addressed. Theories across a range of cognitive domains are reviewed and four kinds of evidence are considered: behavioural, neuropsychological, ontogenetic, and logical. Logical constraints are identified in relation to operating principles of control, access, economy and analogy. The general characteristics of hierarchical structures and their advantages and disadvantages are discussed.     

A Thurstonian Analysis of Preference Change

This paper presents a Thurstonian model for the analysis of preference change. Preferences are expressed in the form of rankings, possibly with ties. A vector-autoregression framework is used to investigate relationships between past and current rankings. It is shown that this approach yields a parsimonious and easily interpretable representation of individual preference differences in time-dependent ranking data. A detailed analysis of the 1992 National Election Study illustrates the proposed approach.     

Online measurement of mental representations of complex spatial decision problems: Comparison of CNET and hard laddering

This paper introduces the online Causal Network Elicitation Technique (CNET), as a technique for measuring components of mental representations of choice tasks and compares it with the more common technique of online ‘hard’ laddering (HL). While CNET works in basically two phases, one in open question format and one as guided linking of attributes and benefits, HL works completely structured with revealed attributes and benefits. Mental representations of two activity travel tasks were collected with both techniques among members of a nationwide Dutch household panel. The results confirm the hypothesis that the revealed format of variables in HL has an effect on the indication of variables as the elicited mental representations are almost twice as big for HL than for CNET. Furthermore, it turned out that CNET is more sensitive in measuring shifts among attributes in the mental representations for situational changes of the activity-travel task.     

Multi‐set factor analysis by means of Parafac2

We consider multi‐set data consisting of observations, k = 1,…, K (e.g., subject scores), on J variables in K different samples. We introduce a factor model for the J × J covariance matrices , k = 1,…, K, where the common part is modelled by Parafac2 and the unique variances , k = 1,…, K, are diagonal. The Parafac2 model implies a common loadings matrix that is rescaled for each k, and a common factor correlation matrix. We estimate the unique variances by minimum rank factor analysis on for each k. The factors can be chosen orthogonal or oblique. We present a novel algorithm to estimate the Parafac2 part and demonstrate its performance in a simulation study. Also, we fit our model to a data set in the literature. Our model is easy to estimate and interpret. The unique variances, the factor correlation matrix and the communalities are guaranteed to be proper, and a percentage of explained common variance can be computed for each k. Also, the Parafac2 part is rotationally unique under mild conditions.