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The Music Therapist\u27s Experience of the Client-Therapist Relationship in Improvisational Voicework: An Interpretive Phenomenological Inquiry
Get PDFThe voice as it is used in clinical improvisation in music therapy can impact the therapeutic relationship between the client and therapist. This study sought to explore music therapists’ perceptions and experience of the client-therapist relationship in the context of improvisational voicework through semi-structured interviews with two experienced Nordoff-Robbins music therapists. The research questions included: What is the music therapist’s experience of the client-therapist relationship in using the voice improvisationally? What is the possible impact of vocal improvisation on the therapeutic process overall? Through an Interpretive Phenomenological Analysis of the data collected in the interviews, three superordinate themes emerged: 1) The Vulnerability of the Voice, 2) Intentionality in Singing and the “Creative Now,” and 3) The Music Is Enough. Findings of the study imply that voicework and vocal improvisation play an important role in the development of the therapeutic relationship in music therapy. The use of the voice can enrich the therapeutic relationship by creating a pathway for communication between the client and therapist that might not otherwise exist. It may also be a unique means of expression for the client. Further research is needed to explore the role of vocal improvisation and voicework in developing the therapeutic relationship across theoretical approaches and client populations
Dear Madam, Dear Sir: Mayor William Gaynor and New York City\u27s Response to the Sinking of Titanic
Get PDFThis article uses the letters of Mayor William Gaynor of New York City to examine how the city and its citizens responded to the sinking of Titanic in 1912
Soaring House Prices Reflect a Shortage of Homes Rather than a New Housing Bubble
Get PDFThe 2020 COVID-19 pandemic has brought to light a flaw in the accounting and pricing of housing services in consumer spending (PCE) and the consumer price index (CPI). The dramatic shifts in housing usage caused by the pandemic have not registered at all in PCE. This paper takes a fresh look at the use of opportunity costs to measure housing services. It shows how the current gauge can miss real changes in services flows. The paper proposes that housing services be measured instead by hedonic methods, using new survey questions added to the Consumer Expenditure Survey (CES) and the CPI
Stories Give Form to a Complex Reality: A Narrative Inquiry of DNP Prepared APRNs During the COVID-19 Pandemic
Get PDFVirtual Presentation
Background: The COVID-19 pandemic changed the landscape of healthcare, yet there is a gap in the literature concerning Doctor of Nursing Practice (DNP) experiences during the COVID-19 pandemic. Objective: To gather an authentic understanding of DNP prepared APRN experiences (stories) caring for patients during the COVID-19 pandemic. Methods: This was a qualitative narrative inquiry study. A purposive sample of DNP prepared APRNs (N=8) were recruited to participate. All interviews were audio recorded, recordings were transcribed, and then the authors crafted each participant’s narrative story. Results: Four overarching themes were identified: Do the Right Thing, Stepping Up, From Here to Reality, and Complex COVID Coping. Twelve subthemes were also identified. Participant stories were profound and indicated that their DNP education prepared them well for the healthcare crisis, but that the emotional toll was difficult. Conclusions/Implications for Practice: This research provides insight into the experiences of DNPs working during the height of the pandemic and elucidates the duty of nursing leaders and educators to appropriately plan, safeguard, and guide DNPs, students, and nurses at all levels. Preparation in epidemiology, public health, disaster planning, tele practice, and wellness is paramount
“Who We Are On Paper”: Celebrating Writing Identity and Diversity With High School Seniors in a Dialogic ELA Classroom
Get PDFGrounded in theory that views language and writing as inextricable from the social event within which it occurs, the purpose of this ethnographic study was to explore how the dialogue produced within the context of a detracked English Language Arts (ELA) classroom contributed to students’ perceptions of their writing identity. The class consisted of a racially, socioeconomically, and academically diverse group of 12th-grade students enrolled in a suburban, public high school. Findings illustrated that writing identity was enacted through multiple iterations of literacy processes embedded in a curriculum that was culturally responsive and implemented through dialogic methods. The analysis of the data from macro, meso, and micro perspectives uncovered two predominant aspects of writing identity. First, students developed understandings of their unique individuality over time that deepened their awareness of writing identity in the writing process, or “who you are on paper.” Second, and interwoven into the first finding, the role of the teacher-student and student-student dialogue through instructional tools, particularly the writer’s notebook and peer review, played an integral role in students’ literacy learning and became another important aspect of writing identity, or “the way you write.” Although research on effective writing methodologies is prolific and valuable, there is less empirical data supporting how students’ cultural backgrounds and educational histories shape their unique writing identities. Implications of this study’s findings suggest that writing identity is a fundamental element in writing development and should be included in existing curricula for the purpose of providing all students with access to effective and equitable writing instruction
A Meaningful Paradox of Color-Blind Racism and Racial Literacy: Understanding the Phenomena of White Women Teachers Educating Students of Color
Get PDFRecognizing school resegregation and the demographic imperative as systemic problems impacting the educational outcomes of students of Color, this study examined the role of White women teachers’ racial views within the sociocultural context of teaching and learning. The purpose of this dissertation was to explore how 15 high school teachers described their lived experiences as educators of Latinx, Black, and Asian students in a racially diverse, public high school on Long Island, New York. This qualitative study was conceptualized through combining the theoretical lens of critical whiteness studies and critical pedagogy utilizing a qualitative phenomenological methodology for data collection, with the framework of color-blind racism added during the data analysis phase. The sample of 15 White women teachers engaged in two or three semi-structured interviews. The emergence of four meaningful paradoxes indicated that although most participants often employed a rhetoric revealing the uncritical endorsement of a color-blind ideology to describe their experiences, White women teachers also indicated that they were learning to see how race impacted them and their students’ lives. These findings provided insights and future directions for K-12 educational institutions and teacher-training programs by suggesting that more efforts are necessary to recognize the signs of color-blind racism, to ensure racial literacy development as an integral part of the education of White women teachers, and to promote positive teacher-student relationships and educational success for students of Color
Automated sleep stage classification in sleep apnoea using convolutional neural networks
Get PDFA sleep disorder is a condition that adversely impacts one\u27s ability to sleep well on a regular schedule. It also occurs as a consequence of numerous neurological sicknesses. These types of disorders can be investigated using laboratory-based polysomnography (PSG) signals. The detection of neurological disorders is exact and efficient thanks to the automated monitoring of sleep relegation stages. This automation method publicly presents a flexible deep learning model and machine learning approach utilizing raw electroencephalogram (EEG) signals. The deep learning model is a Deep Convolutional Neural Network (CNN) that analyses invariant time capacities and frequency actualities and collects assessment adaptations. It also captures the inviolate and long brief length setting conditions between the epochs and the degree of sleep stage relegation.
This method uses an innovative function to calculate data loss and misclassified errors found while training the network for the sleep stage, considering the restrictions found in the publicly available sleep datasets. It is used in conjunction with machine learning techniques to forecast the best approach for the process. Its effectiveness is determined by using two open-source, public databases available from PhysioNet: two recordings with 5402 epoch counts. The technique used in this approach achieves an accuracy of 90.70%, precision of 90.50%, recall of 92.70%, and F-measure of 90.60%. The proposed method is more significant than existing models like AlexNet, ResNet, VGGNet, and LeNet. The comparative study of the models could be adopted for clinical use and modified based on the requirements
Super-resolution reconstruction of brain magnetic resonance images via lightweight autoencoder
Get PDFMagnetic Resonance Imaging (MRI) is useful to provide detailed anatomical information such as images of tissues and organs within the body that are vital for quantitative image analysis. However, typically the MR images acquired lacks adequate resolution because of the constraints such as patients’ comfort and long sampling duration. Processing the low resolution MRI may lead to an incorrect diagnosis. Therefore, there is a need for super resolution techniques to obtain high resolution MRI images. Single image super resolution (SR) is one of the popular techniques to enhance image quality. Reconstruction based SR technique is a category of single image SR that can reconstruct the low resolution MRI images to high resolution images. Inspired by the advanced deep learning based SR techniques, in this paper we propose an autoencoder based MRI image super resolution technique that performs reconstruction of the high resolution MRI images from low resolution MRI images. Experimental results on synthetic and real brain MRI images show that our autoencoder based SR technique surpasses other state-of-the-art techniques in terms of peak signal-to-noise ratio (PSNR), structural similarity (SSIM), Information Fidelity Criterion (IFC), and computational time
Deconstructing the Clinician: An Auto-Ethnographic Study
Get PDFThere is little research focused on uncovering bias in the music therapist. This study utilized autoethnography and was guided by a participatory action research (PAR) lens to explore a music therapist’s experience of and relation to internalized bias and interlocking systems of oppression, such as white supremacy, sexism and ableism. Autoethnography refers to a combination of autobiographical and ethnographic methods. PAR focuses on collective meaning making, redistributing harmful power dynamics, and societal change with a liberatory aim. While I (Nicole) was the primary participant and investigator in the research, Natalia was invited to the study as a co-investigator and participant. Natalia was asked to facilitate three music therapy sessions with myself as the client. We engaged in a reflexive process of collaboration with one another throughout the study. Data included recordings and transcripts of the music therapy sessions, our reflective writings, art, memories, and relevant literature. Data were analyzed through the continuous process of autoethnography. Findings are presented in narrative form, interwoven with writing from both Natalia and myself. This study may contribute to the growing body of research in the larger music therapy community regarding client experience, bias, and systems of oppression
Learning strategies in different environments: Self-regulated learning in traditional and online courses
Get PDFSelf-regulation of academic efforts directly predicts academic performance. However, students engage in regulation of learning in various degrees depending on the content and context. A mixed-methods study was conducted to investigate the intra-student differences of learning strategies in face-to-face and online courses. The results showed statistically significantly higher scores for motivation and study strategies in the classroom setting. The online environment presented more challenges to students, who seemed less autonomous and independent in their learning