Development and Testing of an Instrument to Measure Informatics Knowledge, Skills, and Attitudes Among Entry-Level Nursing Students

Informatics competencies in nursing education have long been and continue to be a concern. This article reports on the development and psychometric testing of the Knowledge, Skills, and Attitudes towards Nursing Informatics (KSANI) Scale to measure these constructs among entry-level nursing students. A measurement instrument was developed based on the Quality and Safety Education for Nurses (QSEN) Institute informatics competencies for pre-licensure students (Cronenwett et al., 2007). Survey data were collected from a convenience sample of 300 undergraduate nursing students attending the 2014 Florida Student Nurses Association’s annual convention. The data were subjected to Cronbach’s test to estimate the level of reliability as internal consistency. At 0.90, the alpha for the overall scale exceeded the 0.70 benchmark for acceptability. The scale items were clustered into the intended three factors – knowledge, skills and attitudes – as well as into the added factor of opportunities. The instrument was found to be sound and appropriate for the target population. Nursing informatics combine the disciplines of nursing science, information science, and computer science (McGonigle & Mastrian, 2015). Ever since the time of Florence Nightingale, one of the critical roles of the registered nurse (RN) has been to collect and interpret data to provide safe and effective patient care. Since the early 1980s, informatics competencies in nursing education have been discussed in nursing literature (Staggers, Gassert, & Curran, 2001). In 1992, the American Nurses Association (ANA, 2015) recognized the importance of technology to nursing practice, identifying nursing informatics as a specialty practice. The 1999 Institute of Medicine (IOM) report calling for a safer health care system identified the use information technology (IT) as a key factor toward meeting this goal. In 2010, the IOM published The Future of Nursing, which recommended making technology an essential component of nursing education. Both the American Association of Colleges of Nursing (AACN, 2008) and the National League for Nursing (NLN, 2008) emphasized that knowledge and skills in information management and patient care technology are critical components in nursing education and accreditation. Skiba, Connors, and Jeffries (2008) identified a lack of informatics competencies in nursing education prior to 2008. Since that time, the American Association of Colleges of Nursing (AACN) and the Robert Wood Johnson Foundation (RWJF) have partnered to support the Quality and Safety Education for Nurses (QSEN) Initiative (AACN, 2016). One of the components of the QSEN Initiative was the development of competencies in various areas including informatics. This research contributes to the development of a reliable and valid instrument based on the QSEN competencies to test the informatics knowledge, skills, and attitudes of current RN students in Florida

Development and Testing of an Instrument to Measure Informatics Knowledge, Skills, and Attitudes Among Entry-Level Nursing Students

Informatics competencies in nursing education have long been and continue to be a concern. This article reports on the development and psychometric testing of the Knowledge, Skills, and Attitudes towards Nursing Informatics (KSANI) Scale to measure these constructs among entry-level nursing students. A measurement instrument was developed based on the Quality and Safety Education for Nurses (QSEN) Institute informatics competencies for pre-licensure students (Cronenwett et al., 2007). Survey data were collected from a convenience sample of 300 undergraduate nursing students attending the 2014 Florida Student Nurses Association’s annual convention. The data were subjected to Cronbach’s test to estimate the level of reliability as internal consistency. At 0.90, the alpha for the overall scale exceeded the 0.70 benchmark for acceptability. The scale items were clustered into the intended three factors – knowledge, skills and attitudes – as well as into the added factor of opportunities. The instrument was found to be sound and appropriate for the target population. Nursing informatics combine the disciplines of nursing science, information science, and computer science (McGonigle & Mastrian, 2015). Ever since the time of Florence Nightingale, one of the critical roles of the registered nurse (RN) has been to collect and interpret data to provide safe and effective patient care. Since the early 1980s, informatics competencies in nursing education have been discussed in nursing literature (Staggers, Gassert, & Curran, 2001). In 1992, the American Nurses Association (ANA, 2015) recognized the importance of technology to nursing practice, identifying nursing informatics as a specialty practice. The 1999 Institute of Medicine (IOM) report calling for a safer health care system identified the use information technology (IT) as a key factor toward meeting this goal. In 2010, the IOM published The Future of Nursing, which recommended making technology an essential component of nursing education. Both the American Association of Colleges of Nursing (AACN, 2008) and the National League for Nursing (NLN, 2008) emphasized that knowledge and skills in information management and patient care technology are critical components in nursing education and accreditation. Skiba, Connors, and Jeffries (2008) identified a lack of informatics competencies in nursing education prior to 2008. Since that time, the American Association of Colleges of Nursing (AACN) and the Robert Wood Johnson Foundation (RWJF) have partnered to support the Quality and Safety Education for Nurses (QSEN) Initiative (AACN, 2016). One of the components of the QSEN Initiative was the development of competencies in various areas including informatics. This research contributes to the development of a reliable and valid instrument based on the QSEN competencies to test the informatics knowledge, skills, and attitudes of current RN students in Florida

Global Systems Science and Policy

The vision of Global Systems Science (GSS) is to provide scientific evidence and means to engage into a reflective dialogue to support policy-making and public action and to enable civil society to collectively engage in societal action in response to global challenges like climate change, urbanisation, or social inclusion. GSS has four elements: policy and its implementation, the science of complex systems, policy informatics, and citizen engagement. It aims to give policy makers and citizens a better understanding of the possible behaviours of complex social systems. Policy informatics helps generate and evaluate policy options with computer-based tools and the abundance of data available today. The results they generate are made accessible to everybody—policymakers, citizens—through intuitive user interfaces, animations, visual analytics, gaming, social media, and so on. Examples of Global Systems include epidemics, finance, cities, the Internet, trade systems and more. GSS addresses the question of policies having desirable outcomes, not necessarily optimal outcomes. The underpinning idea of GSS is not to precisely predict but to establish possible and desirable futures and their likelihood. Solving policy problems is a process, often needing the requirements, constraints, and lines of action to be revisited and modified, until the problem is ‘satisficed’, i.e. an acceptable compromise is found between competing objectives and constraints. Thus policy problems and their solutions coevolve much as in a design process. Policy and societal action is as much about attempts to understand objective facts as it is about the narratives that guide our actions. GSS tries to reconcile these apparently contradictory modes of operations. GSS thus provides policy makers and society guidance on their course of action rather than proposing (illusionary) optimal solutions

Scaling Behavior of Human Locomotor Activity Amplitude: Association with Bipolar Disorder

Scale invariance is a feature of complex biological systems, and abnormality of multi-scale behaviour may serve as an indicator of pathology. The hypothalamic suprachiasmatic nucleus (SCN) is a major node in central neural networks responsible for regulating multi-scale behaviour in measures of human locomotor activity. SCN also is implicated in the pathophysiology of bipolar disorder (BD) or manic-depressive illness, a severe, episodic disorder of mood, cognition and behaviour. Here, we investigated scaling behaviour in actigraphically recorded human motility data for potential indicators of BD, particularly its manic phase. A proposed index of scaling behaviour (Vulnerability Index [VI]) derived from such data distinguished between: [i] healthy subjects at high versus low risk of mood disorders; [ii] currently clinically stable BD patients versus matched controls; and [iii] among clinical states in BD patients

Neonicotinoids: insecticides acting on insect nicotinic acetylcholine receptors.

Imidacloprid is increasingly used worldwide as an insecticide. It is an agonist at nicotinic acetylcholine receptors (nAChRs) and shows selective toxicity for insects over vertebrates. Recent studies using binding assays, molecular biology and electrophysiology suggest that both alpha- and non-alpha-subunits of nAChRs contribute to interactions of these receptors with imidacloprid. Electrostatic interactions of the nitroimine group and bridgehead nitrogen in imidacloprid with particular nAChR amino acid residues are likely to have key roles in determining the selective toxicity of imidacloprid. Chemical calculation of atomic charges of the insecticide molecule and a site-directed mutagenesis study support this hypothesis