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Aims To report a systematic review of the psychometric properties of self-report instruments to identify the symptoms of anxiety in pregnancy to help clinicians and researchers select the most suitable instrument. Background Excessive anxiety in pregnancy is associated with adverse birth outcomes, developmental and behavioural problems in infants and postnatal depression. Despite recommendations for routine psychological assessment in pregnancy, the optimal methods to identify anxiety in pregnancy have not been confirmed. Design Psychometric systematic review. Data sources A systematic literature search of the multiple databases (1990-September 2014). Review methods Identification of self-report instruments to measure anxiety in pregnancy using COSMIN guidelines to assess studies reporting a psychometric evaluation of validity and reliability. Results Thirty-two studies were included. Studies took place in the UK, Australia, Belgium, Canada, Germany, Italy, Scandinavia, Spain and the Netherlands. Seventeen different instruments were identified. Measures of validity were reported in 19 papers and reliability in 16. The overall quality of the papers was rated as fair to excellent using the COSMIN checklist. Only one paper scored excellent in more than one category. Conclusion Many instruments have been adapted for use in different populations to those for which they were designed. The State Trait Anxiety Inventory, Edinburgh Postnatal Depression Scale and the Hospital Anxiety and Depression Scale have been tested more frequently than other instruments, yet require further assessment to confirm their value for use in pregnancy. [ABSTRACT FROM AUTHOR]

To identify the patient classification systems used to classify nursing intensity in the assessment of nursing staffing resources currently used in home health care, with a special emphasis on validity, reliability and staff allocation. Scoping review of internationally published and grey literature, based on a methodological framework by Arksey and O'Malley. Searches of the electronic databases Cinahl, Medline, Embase and SweMed, the websites Google and Google Scholar and hand searches of reference lists occurred. Eligibility criteria included (A) a focus on patient classification systems measuring nursing intensity and workload in home health care and (B) published in English between January 2007 and March 2019. In level one testing two team members screened titles and abstracts, in level two testing two team members determined which papers should undergo a full text review. Data were extracted using structured extraction by one team member and verified by two other members. Thirteen peer-reviewed articles and grey literature documents were identified, from Canada, Ireland, the UK, the USA, Scotland, Turkey and the Netherlands. Four patient classification systems had been tested for both validity and reliability. Validity was tested through face validity, predictive validity, concurrent validity or content validity index. Reliability was tested through stability, internal consistency, observer agreement or inter rater reliability. One patient classification system had been tested only for reliability, through interrater reliability and observer agreement. Two patient classification systems had been evaluated through summative evaluation; one qualitatively through focus group interviews and one through semi-structured interviews. Only one patient classification system had been validity and reliability tested and evaluated. Overall, the patient classification systems in the included papers (13) were considered to have benefits and to be appropriate for the measurement of patients' needs, workload and allocation of staff, although specific information was not always given. Little has been published on validity or reliability tested patient classification systems linked to staffing allocation in home health care in the past decade. Limited research was seen where a patient classification system was considered to be fully operational in home health care. [ABSTRACT FROM AUTHOR]