Social support predicted quality of life in people receiving haemodialysis treatment: A cross-sectional survey.

Aims: To examine levels of social support and quality of life (QOL) and to examine the association between social support and QOL in patients receiving haemodialysis (HD) treatment. Design: A cross-sectional study. Method: social support and QOL were measured using the Multidimensional Scale of Perceived social Support (MSPSS) and the World Health Organization QOL-BREF questionnaires, respectively. A convenience sample of 195 patients receiving HD from different dialysis units across Jordan completed the questionnaires. Results: Respondents scored highest on the social relationships domain of QOL (55.5 SD 21.4) compared with the lowest mean scores of the physical and environmental domains (48.6 SD 20.4; 46.2 SD 17.3, respectively). social support had a positive significant association with quality of life. Multiple linear regression identified age and social support as influencing factors, explaining 24.6% of the total variance in the social domain of quality of life.Understanding the relationship between social support and QOL in patients receiving HD may provide guidance to the healthcare providers, family members and social services about the importance of social support to this group of patients.

Examining the Relationship Between Nursing Informatics Competency and the Quality of Information Processing.

The purpose of this study was to examine nursing informatics competency and the quality of information processing among nurses in Jordan. The study was conducted in a large hospital with 380 registered nurses. The hospital introduced the electronic health record in 2010. The measures used in this study were personal and job characteristics, self-efficacy, Self-Assessment Nursing Informatics Competencies, and Health Information System Monitoring Questionnaire. The convenience sample consisted of 99 nurses who used the electronic health record for at least 3 months. The analysis showed that nine predictors explained 22% of the variance in the quality of information processing, whereas the statistically significant predictors were nursing informatics competency, clinical specialty, and years of nursing experience. There is a need for policies that advocate for every nurse to be educated in nursing informatics and the quality of information processing.