4^th International Conference on Palliative Care, Medicine and Hospice Nursing August 27-28, 2018 Boston, Massachusetts, USA

Dale M. Hilty, Associate Professor, received his PhD in counseling psychology from Department of Psychology at the Ohio State University. He has published studies in the areas of psychology, sociology, and religion. Between April 2017 and April 2018, his ten research teams published 55 posters at local, state, regional, national, and international nursing conferences.

Halter and colleagues (2017) reviewed primary research articles using the Nursing Turnover Cost Calculation Methodology and found the turnover rate was 27% (Duffield et al, 2014) in the United States. Halter and colleagues (2017) summarized Li and Jones\' (2013, p. ) findings: \"This review was based on ten studies, eight of which were in acute hospital settings, all conducted in the USA, with one also in each of Australasia and Canada. The review reported costs of per nurse turnover ranging from $10,098 to $88,000 ....\"\r\n\r\nThe purpose of this educational intervention was to determine whether high and moderate-low scores on self-efficacy differentiated coping skills with a sample of nursing students. Instrumentation: Self-Efficacy (Schwarzer & Jerusaslem, 1995), Wooden\'s Competitive Greatness (Hilty, 2017) construct (i.e., being the best you can be when your best is needed, continuous self-improvement, appreciating difficult challenges), and Greenglass\' et al. (1999) proactive coping, reflective coping, and strategic planning. If nursing students reported different levels of continuous self-improvement and coping skills in relation to self-efficacy, it may be possible to track these students following graduation to determine the relationship between turnover rates and these research constructs.\r\n\r\nA sample of Bachelor of Science in Nursing (BSN) traditional students were divided into two groups using the self-efficacy scales. Hypothesis 1: There would be a difference between self-efficacy (high and moderate-low scoring groups) when compared to the Proactive Coping, Reflective Coping, Strategic Planning scales (SPSS 25, Independent t-test). Hypothesis 2: A difference would be found using self-efficacy as the dependent variable and competitive greatness (i.e., continuous self-improvement) as the predicator variable (SPSS 25, linear regression). \r\n \r\n\r\n\r\nIndependent t-test (N=61) analyses found significant differences between Proactive Coping (p=.001 ), Reflective Coping (p=.001), and Strategic Planning (p=.001) scales. The linear regression analysis confirmed the hypothesis 2 prediction and produced a correlation between self-efficacy and competitive greatness of .515 (r square = .265) which is significant (F (1, 59)=21.307, p=.001). Higher levels of self-efficacy are associated with higher levels of continuous self-improvement.\r\n

Dale M. Hilty, Associate Professor, received his PhD in counseling psychology from Department of Psychology at the Ohio State University. He has published studies in the areas of psychology, sociology, and religion. Between April 2017 and April 2018, his ten research teams published 55 posters at local, state, regional, national, and international nursing conferences.

Simpson and colleagues (Simpson, 1990; Simpson, Rholes, & Phillips, 1996) developed the Adult Attachment Questionnaire (AAQ) which was one of the first quantitative instruments. Exploratory factor analysis found support for two common factors (attachment anxiety, attachment avoidance). AAQ used 17 items. Graham and Uterschute (2015) reported .78 coefficient alpha reliability estimates for both common factors. Carver and colleagues (Carver, 1997; Kim & Carver, 2007) developed a quantitative instrument named the Measure of Attachment Quality (MAQ) which consisted of 13 items designed to measure significant other relationships. Exploratory factor analysis found support for three common factors: secure, anxious, and avoidant (Kim & Carver, 2007). \r\n\r\nThe purpose of this educational intervention was to design a questionnaire that would measure attachment styles, that could be applied to the professional relationships between nursing students and their patients. A quantitative instrument (i.e., Nursing Attachment Styles Questionnaire; NASQ) was designed with 33 items with 11 items measuring secure, anxious, and avoidant attachment styles. \r\n\r\nThe participants (N=247) were BSN nursing students. Hypothesis 1: Determine whether attachment measured with the NASQ items would be a multi-dimensional construct (i.e., two or more common factors). This hypothesis would be tested by using exploratory principal axis factor analysis (EPAFA). Hypothesis 2: Determine if the reliability estimate(s) would be greater than .80 for engagement common factors. Hypothesis 3: Determine whether secure, anxious, and avoidant attachment as measured by the NASQ, AAQ, and MAQ scales were significantly correlated with the theoretically designed constructs.\r\n\r\n \r\n\r\n\r\nUndergraduate BSN nursing students (N=247) responses were analyzed via EPAFA with a oblimin rotation. Three common factors (secure, anxious, avoidant) accounted for 64% of the variance (eigenvalues = 12.455, 5.71, 2.963). Each of the theoretically designed items loaded on the respective common factors. Coefficient alpha reliability estimates were .93 (secure), .933 (anxious), and .947 (avoidant). Correlations coefficients were significantly correlated among the NASQ, AAQ, and MAQ scales.

Beverly Gish, Assistant Professor, has been a nurse for 40 years and have diverse career experiences in direct patient care, staff education, nursing management, and finally nursing education. I started my career on a busy gynecology/oncology unit, moving to critical care, then the emergency department, and finally a specialty in neurosurgery. Currently, I have returned to direct patient care and practice as a certified nurse practitioner (CNP) in a primary care (community clinic) setting. I love the insight it gives me in the teaching environment. Professionally, I have fifteen years of teaching nursing.

Student engagement has been defined as “the level of interest demonstrated by students, how they interact with each other in the course, and their motivation to learn about the topics” (Gray & DiLoreto, 2016, p. 5). Online learning environments are challenged to develop strategies that will engage students, to improve student retention and maximize student achievement of course objectives. Therefore, different online learning strategies require assessment to determine their effectiveness at enhancing student engagement.\r\n\r\nHilty, Gill-Rocha, Parkinson, Blackford, & Cook (2018) evaluated the psychometric properties of the Burch et al., (2014) 63-item \r\nStudent Engagement Survey (SES). Exploratory principal axis factor analysis (EPAFA) was used to determine the number of underlying factors. Using the scree test to determine the number of factors, the EPAFA with an oblimin rotation suggested four factors. The scree test indicated four factors (eigenvalues: 17.176, 3.807, 2.942, and 2.151) accounting for 63.6% of the variance. Forty-one (41) of the 63 items loaded on one of the physical engagement, cognitive engagement, deep learning engagement, and engagement skills factors. Coefficient alpha reliability estimates were .921 (Physical), .961 (Cognitive), .905 (Deep Learning), and .937 (Engagement Skills). \r\n\r\nMasters level graduate nursing students completed the 41 questions designed to measure student engagement. Advanced Pathophysiology students completed an educational intervention based on a passive learning and active learning modules for this online course. Learning activities, such as textbook readings, videos and quizzes, were the same for all modules. The difference was in the discussion of the case studies. \r\n\r\nUsing SPSS 25, the dependent t-test analyzed the passive and active learning approaches by comparing student responses to the physical, cognitive, deep learning, and engagement skill factors. First, there was no statistical (p=.204) difference between the passive and active learning on the physical engagement factor/scale. \r\n \r\n\r\nSecond, there was a statistical (p=.019) difference on the cognitive engagement factor/scale. Third, there was a statistical (p=.002) difference on the deep learning engagement factor/scale. Fourth, there was a statistical (p=.022) difference on the engagement skills factor/scale. These findings demonstrated the students were significantly more engaged while completing the active learning modules.\r\n\r\nUsing SPSS 25, the dependent t-test analyzed the passive and active learning approaches by comparing student responses to the physical, cognitive, deep learning, and engagement skill factors. First, there was no statistical (p=.204) difference between the passive and active learning on the physical engagement factor/scale. Second, there was a statistical (p=.019) difference on the cognitive engagement factor/scale. Third, there was a statistical (p=.002) difference on the deep learning engagement factor/scale. Fourth, there was a statistical (p=.022) difference on the engagement skills factor/scale. These findings demonstrated the students were significantly more engaged while completing the active learning modules.

Clemente Amoroso: Clemente Amoroso is a music therapist, a sociologist and a trainer; he performs music therapy as a freelancer, in his own studio and in agencies and institutions. He is the scientific coordinator of Musicaperta-sound, research, therapy-music therapy for neuro-psychiatric pathologies and autism spectrum disorders of Caserta (Italy). Since 2008 at the Department of Mental Health of the ASL of Caserta. he is Music therapy teacher and sociology of music.He has studied at University of Naples Federico II, University of Ferrara, University of Music and Dramatic Arts Mozarteum of Salzburg, CEP music therapy school at Assisi.\r\nElisabetta Piras: Elisabetta Piras begins to study piano in childhood, carrying out classical studies in parallel. She then graduated in musical disciplines at the Alma Mater Studiorum- University of Bologna, and specialized in music education and research methodology in the field of musical education. At the moment teaches piano and music education, in many schools, in the University of Bologna and in the Italian Conservatories of Music, and she also currently performing in concerts as a soloist and in chamber ensembles.She participates in international conferences as musicologist (Vienna, Graz, Porto Alegre, Salvador de Bahia, Porto, Coventry, Bologna, Rimini, Genova, Roma, Trento, Athens, Madrid, Aveiro, Bejging etc.) and she writes for reviews and books, focusing on contemporary music and music education, particularly from a psychological point of view.

Statement of the problem: Music has always considered a therapeutic element for the human being. There is a wide range of scientific literature on this subject, and the Music Therapy is a recognized discipline. In general we can say that Music Therapy is a non-verbal psychotherapeutic method that uses musical interaction as a means of communication and expression. The purpose of the therapy is to help people with psychophysical illnesses, as well as social disease, to develop relationships and to facilitate the resolution of problems that can’t be dealt with by verbalization. The purpose of the present study is to present a music therapy experience in the contest of hospice, starting from the questions: Are there any significant benefits in combining music therapy with standard care? Which are the indicators that allow to identify them? A reflection has made, focused on a musical activities carried out in a nursery home for elderly people. Findings: The results have shown benefits from a qualitative point of view, which pertain to arousal, socialization e.g.. From a quantitative point of view, there was a variation in the need for administration of benzodiazepine in different subjects. Conclusion & Significant: This last observation encourages us to deepen the research in a quantitative sense. What we want to highlight is the thinking that led to this acquisitions. First results come out an observation of the music therapeutic action in relation to the clinical and social situation as a whole, experienced in a natural situation, in consideration of the general well-being of the person and the material and economic organization of the Institution.