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Summary: Restless legs syndrome (RLS) is a common neurological disorder characterised by an urge to move arms and legs, usually associated with discomfort, pain, motor restlessness, and sleep disturbance. An individually adapted treatment is needed but difficult to optimise, which makes shared decision‐making (SDM) important. However, brief validated instruments on how patients with RLS perceive their involvement in treatment decisions are lacking. Therefore, the aim was to validate two instruments, SURE (Sure of myself, Understand information, Risk–benefit ratio, Encouragement, i.e., to assess decisional conflict) and CollaboRATE (brief patient survey focused on SDM, i.e., to assess SDM), in patients with RLS. A cross‐sectional design, including 788 participants with RLS (65% females, mean [SD] age 70.8 [11.4] years) from a national patient organisation for RLS, was used. A postal survey was sent out to collect data regarding weight, height, comorbidities, demographics, and RLS‐related treatment data. The following instruments were included: the SURE, CollaboRATE, Restless Legs Syndrome‐6 Scale, and eHealth Literacy Scale. Confirmatory factor analysis and Rasch models were used to assess the validity and reliability of the SURE and CollaboRATE. Measurement invariance, unidimensionality, and differential item functioning (DIF) across age, gender, and medication groups were assessed. The SURE and CollaboRATE were both identified as unidimensional instruments with satisfactory internal consistency. No DIF across age and gender was identified, while significant DIF was observed for both the SURE and CollaboRATE regarding medication use categories. However, both the SURE and CollaboRATE are potential instruments to be used in research, but also as reflection tools by healthcare professionals, patients, and students to explore and assess SDM, and support its development in clinical care. [ABSTRACT FROM AUTHOR]

Summary Biphasic sleep, characterized by nighttime sleep plus daytime napping, has demonstrated some cognitive, health and performance impacts when compared with consolidated monophasic sleep. This motivated the development and validation of the Biphasic Sleep Scale, reported in this paper. Scale development involved a literature review, expert input and individual interviews. The 16‐item Biphasic Sleep Scale was then administered to an international online sample (n = 6965) alongside well‐established validated sleep scales. To ensure a robust evaluation of the Biphasic Sleep Scale, the sample was divided into two parts: with 15% (n = 1000) of the participants allocated to the exploratory analytic phase; and the remaining 85% (n = 5965) reserved for confirmatory analyses. Psychometric evaluation included both exploratory and confirmatory factor analysis, reliability analysis, correlations, network analysis, and item response theory. Exploratory factor analysis indicated a three‐factor structure assessing daytime napping as to likelihood, consequences and effect on nighttime sleep. Confirmatory factor analysis largely confirmed this model with no sex invariance. The three‐factor structure showed adequate fit. The Biphasic Sleep Scale demonstrated good internal consistency (α = 0.88, Ω = 0.89). Network analysis revealed varying centrality and connectivity of items. Item response theory found items covering a range of biphasic sleep levels. Significant positive correlations with sleep criteria provided evidence for convergent validity. Further testing is warranted to confirm the factor structure, refine model parsimony, and establish clinical utility. With additional validation, it is hoped that the Biphasic Sleep Scale will become a widely utilized tool. [ABSTRACT FROM AUTHOR]

Aims/Introduction: The objective of this study was to translate and validate an Iranian version of the Diabetes Quality of Life (DQOL) questionnaire in an Iranian population of males and females with a diagnosis of type 2 diabetes. Materials and Methods: A total of 503 patients with type 2 diabetes were recruited from nine diabetes clinics across several Iranian cities. A standard backward and forward translation procedure was used to convert the English version of the DQOL into the Iranian language (Persian). Internal consistency, convergent validity, known group comparison, confirmatory factor analysis (CFA) and factorial invariance were applied for the assessment of psychometric properties of the translated version. Results: The translated version of the DQOL showed adequate internal consistency reliabilities for all subscales (Cronbach's α >0.70). CFA confirmed the underlying domain structure to be the same as for the original English version, therefore supporting the factorial validity of the translated questionnaire. In addition, questionnaire responsiveness showed good sensitivity to interventions. Conclusions: In conclusion, the translated Iranian version of DQOL has shown high internal reliability and good construct validity, and can potentially be applied as an assessment tool for health-related quality of life in patients with diabetes. (J Diabetes Invest, doi: 10.1111/j.2040-1124.2012.00217.x, 2012) [ABSTRACT FROM AUTHOR]

Summary: For patients with cancer, sleep disturbance is commonplace. Using classical test theory and Rasch analyses, the present study compared two commonly used psychometric instruments for insomnia – Athens Insomnia Scale and Insomnia Severity Index – among patients with advanced cancer. Through convenience sampling, patients with cancer at stage III or IV (n = 573; 326 males; mean age = 61.3 years; SD = 10.7) from eight oncology units of university hospitals in Iran participated in the study. All the participants completed the Athens Insomnia Scale, Insomnia Severity Index, Edmonton Symptom Assessment Scale, Hospital Anxiety and Depression Scale, General Health Questionnaire‐12, Epworth Sleepiness Scale and Pittsburgh Sleep Quality Index. Additionally, 433 participants wore an Actigraph device for two continuous weekdays. Classical test theory and Rasch analysis both supported the construct validity for Athens Insomnia Scale (factor loadings from confirmatory factor analysis = 0.61–0.87; test–retest reliability = 0.72–0.82; infit mean square = 0.81–1.17; outfit MnSq = 0.79–1.14) and for Insomnia Severity Index (factor loadings from confirmatory factor analysis = 0.61–0.81; test–retest reliability = 0.72–0.82; infit mean square = 0.72–1.14; outfit mean square = 0.76–1.11). Both Athens Insomnia Scale and Insomnia Severity Index had significant associations with Edmonton Symptom Assessment Scale, Hospital Anxiety and Depression Scale, General Health Questionnaire‐12, Epworth Sleepiness Scale and Pittsburgh Sleep Quality Index, as well as having good sensitivity and specificity. Significant differences in the actigraphy measure were found between insomniacs and non‐insomniacs based on Athens Insomnia Scale or Insomnia Severity Index score. With promising results, healthcare providers can use either Athens Insomnia Scale or Insomnia Severity Index to understand the insomnia of patients with advanced cancer. [ABSTRACT FROM AUTHOR]