Search

Music-evoked autobiographical memories (MEAMs) are typically elicited by music that listeners have heard before. While studies that have directly manipulated music familiarity show that familiar music evokes more MEAMs than music listeners have not heard before, music that is unfamiliar to the listener can also sporadically cue autobiographical memory. Here we examined whether music that sounds familiar even without previous exposure can produce spontaneous MEAMs. Cognitively healthy older adults (N = 75, ages 65-80 years) listened to music clips that were chosen by researchers to be either familiar or unfamiliar (i.e., varying by prior exposure). Participants then disclosed whether the clip elicited a MEAM and later provided self-reported familiarity ratings for each. Self-reported familiarity was positively associated with the occurrence of MEAMs in response to familiar, but not the unfamiliar, music. The likelihood of reporting MEAMs for music released during youth (i.e., the "reminiscence bump") relative to young adulthood (20-25 years) included both music released during participants' adolescence (14-18 years) and middle childhood (5-9 years) once self-reported familiarity was accounted for. These developmental effects could not be accounted for by music-evoked affect. Overall, our results suggest that the phenomenon of MEAMs hinges upon both perceptions of familiarity and prior exposure.

Background: Healthcare worker (HCW)-patient communication is an essential element of every patient’s journey, and evidence links good communication with favourable patient experiences and outcomes. Simulation-based training (SBT) is a promising and effective tool to improve such communication. Aim: To develop a bilingual SBT programme in communication skills for all HCWs in an academic tertiary hospital, to improve patient care, experiences and outcomes. Methods: This was a quasi-experimental design, conducted in 2018 at King Abdulaziz University (KAU). We designed and delivered a bilingual, simulation-based, full-day course for HCWs (both clinical and administrative), and measured its impact by comparing pre- and post-course test scores, participant feedback, and instructor performance satisfaction indices. Results: We trained 318 HCWs over 15 days, using 10 instructors. Post-test scores showed individual and overall improvement. The average scores were 26.6% (14-40%) for the pre-test and 55.8% (37-70%) for the post-test, with an average improvement of 29% (P

Background: In the United States, the current 6-year completion rate in engineering is a mere 54% among full-time students who enter a 4-year course. Researchers have identified many reasons why students leave engineering, including academic difficulties and poor teaching. However, the problems experienced by the departing students are also experienced by students who persist in engineering. Why do some students persist in engineering while others depart? Purpose: We sought to better understand persisters by investigating their responses to failure experiences. We left the definition of failure up to the students, who described experiences such as failing exams, failing courses, and temporarily abandoning their degree programs. Design/Method: We interviewed 26 undergraduate engineering students who had persisted in engineering after failing a required technical course. Using thematic analysis, we analyzed the students' responses to their failure experiences and developed themes to describe their responses. Results: We constructed four themes to describe students' responses to failure experiences: unresponsive, avoidant, floundering, and rebounding. Conclusions: Since failure events are common among engineering students--even those who persist--we recommend that the engineering education community work toward removing the stigma traditionally associated with failure by normalizing failure as an opportunity for growth. We also recommend that faculty and administrators revise academic policies to promote student resilience and to enable learning from failure.

The neuroscience of music and music-based interventions (MBIs) is a fascinating but challenging research field. While music is a ubiquitous component of every human society, MBIs may encompass listening to music, performing music, music-based movement, undergoing music education and training, or receiving treatment from music therapists. Unraveling the brain circuits activated and influenced by MBIs may help us gain better understanding of the therapeutic and educational values of MBIs by gathering strong research evidence. However, the complexity and variety of MBIs impose unique research challenges. This article reviews the recent endeavor led by the National Institutes of Health to support evidence-based research of MBIs and their impact on health and diseases. It also highlights fundamental challenges and strategies of MBI research with emphases on the utilization of animal models, human brain imaging and stimulation technologies, behavior and motion capturing tools, and computational approaches. It concludes with suggestions of basic requirements when studying MBIs and promising future directions to further strengthen evidence-based research on MBIs in connections with brain circuitry.SIGNIFICANCE STATEMENT Music and music-based interventions (MBI) engage a wide range of brain circuits and hold promising therapeutic potentials for a variety of health conditions. Comparative studies using animal models have helped in uncovering brain circuit activities involved in rhythm perception, while human imaging, brain stimulation, and motion capture technologies have enabled neural circuit analysis underlying the effects of MBIs on motor, affective/reward, and cognitive function. Combining computational analysis, such as prediction method, with mechanistic studies in animal models and humans may unravel the complexity of MBIs and their effects on health and disease.

In light of both social and ABET expectations, engineering educators need to consider how to effectively infuse engineering ethics education into current engineering curricula. This article describes our initial efforts in that realm. We considered how to improve ethics education in engineering through establishing an academic-industry partnership, which facilitated conversation between engineering faculty members and practicing engineers in industry. We formed a College-level Ethics Advisory Council with representation from industry partners across all 13 engineering departments in Purdue's College of Engineering. As the first official activity, we held an Ethics Advisory Council Workshop to define common goals and share mutual expectations for long-term relationships. This article shares some basic information about the academic-industry partnership and outputs from the Ethics Advisory Council Workshop. We also discuss lessons we learned from the initial work on the partnership, including limitations and other considerations important for potential adopters of such a strategy at their institution. This article can provide insights to engineering educators who are interested in adopting the academic-industry partnership approach to facilitate direct conversations between academia and industry, especially for better engineering ethics education.

In introductory computer programming courses, students experience a range of emotions. Students often experience anxiety and frustration when they encounter difficulties in writing programs. Continued frustration can discourage students from pursuing engineering and computing careers. Although prior research has shown how emotions affect students' motivation and learning, little is known about students' emotions in programming courses. In this qualitative study of first-year engineering students taking an introductory programming course, we examined the emotions that these students experienced during programming tasks and the reasons for experiencing those emotions. Our study was grounded in the control-value theory of achievement emotions. Each research participant came to two laboratory sessions: a programming session and a retrospective think-aloud interview session. In the programming session, each participant worked individually on programming problems. We collected screen capture, biometrics, and survey responses. In the interview session, each participant watched a video of their actions during the programming session. After every 2 minutes of viewing, the participants reported the emotions that they had experienced during this 2-minute period. We performed a thematic analysis of the interview data. Our results indicate that the participants experienced frustration most frequently. Sometimes they experienced multiple emotions. For example, one participant felt annoyed because she had made a mistake, but she felt joy and pride when she fixed the mistake. To promote student learning, educators should take students' emotions into account in the design of curriculum and pedagogy for introductory programming courses.

Background: Coronavirus disease 2019 (COVID-19)-associated mortality is predominantly due to respiratory failure. However, risk factors and predictive models for disease progression in patients with COVID-19 are not consistent across the globe. In this study, we aimed to assess the risk factors associated with intensive care (ICU) admission and mortality in patients with COVID-19 pneumonia. Methods: Information was retrieved from the database of all patients admitted with COVID-19 pneumonia between March 2020 and July 2020 at a tertiary care center in Saudi Arabia. The patients’ demographic, clinical, laboratory and radiological characteristics were analyzed. Results: Of 1054 patients admitted with PCR proven COVID-19, 254 patients (24%) with radiological evidence of pneumonia were enrolled. The median age was 55, with 25.6% above 65 years and 55.1% males. The comorbidities included hypertension (45%), diabetes (43%), dyslipidemia (24%), solid organ and bone marrow transplantation (14.5%), malignancy (13.4%), ischemic heart disease (10.6%) and chronic kidney disease (9.4%). The mortality rate was 4.7%, and 22.8% were admitted to the ICU.The risk factors for ICU admission were> 65 years of age (RR: 1.74, CI 95%, 1.10–2.74, p = 0.017), diabetes melitus (RR: 1.66, CI 95% 1.06–2.62, p = 0.028), heart failure (RR: 2.51, CI 95%, 1.28–4.93, p = 0.007), respiratory rate> 25 (RR: 2.75, CI 95%, 1.66–4.55, p 140 (RR: 1.89, CI 95%, 1.14–3.13, p = 0.013).The risk factors for mortality were> 65 years of age (RR: 5.82, CI 95%, 1.81–18.68, p = 0.003), upper lobe involvement on chest radiography (RR:4.40, CI 95%, 1.22–15.86, p = 0.016), diffuse chest computed tomography changes (RR: 7.36, CI 95%, 2.31–23.46, p 25 (RR: 3.94, CI 95%, 1.32–11.78 p = 0.023), oxygen saturation

Laboratory kits allow students to take home laboratory equipment to complete experiments on their own time. Because of the lower cost, laboratory kits expand access to hands-on experiences for online courses and to budget-strapped campuses. Although students like laboratory kits, no previous studies compared student learning objectives on assignments using laboratory kits with existing laboratory equipment. We conducted a quasi-experiment to compare students' achievement of learning and their experience in the instructional laboratory for two offerings of an introductory control systems course. Half of the laboratory sections in each offering used the existing equipment, while the other sections used a new kit. The objectives of the laboratory experiments were the same for both types of equipment, and the instructions were as close as possible. In order to assess the students' achievement of the learning objectives and understand the students' experience, we collected a variety of data, including graded laboratory reports, end-of-semester surveys, focus groups, student reflections after each laboratory, midterm exam scores, final exam scores, and control systems concept inventory scores. This comprehensive assessment method may be of independent interest. Based on the data collected, we found no significant differences in the achievement of the learning objectives or in the students' experiences.

Groove, or the pleasurable urge to move to music, offers unique insight into the relationship between emotion and action. The predictive coding of music model posits that groove is linked to predictions of music formed over time, with stimuli of moderate complexity rated as most pleasurable and likely to engender movement. At the same time, listeners vary in the pleasure they derive from music listening: individuals with musical anhedonia report reduced pleasure during music listening despite no impairments in music perception and no general anhedonia. Little is known about musical anhedonics' subjective experience of groove. Here we examined the relationship between groove and music reward sensitivity. Participants (n = 287) heard drum-breaks that varied in perceived complexity, and rated each for pleasure and wanting to move. Musical anhedonics (n = 13) had significantly lower ratings compared to controls (n = 13) matched on music perception abilities and general anhedonia. However, both groups demonstrated the classic inverted-U relationship between ratings of pleasure & move and stimulus complexity, with ratings peaking for intermediately complex stimuli. Across our entire sample, pleasure ratings were most strongly related with music reward sensitivity for highly complex stimuli (i.e., there was an interaction between music reward sensitivity and stimulus complexity). Finally, the sensorimotor subscale of music reward was uniquely associated with move, but not pleasure, ratings above and beyond the five other dimensions of musical reward. Results highlight the multidimensional nature of reward sensitivity and suggest that pleasure and wanting to move are driven by overlapping but separable mechanisms.

Why do humans make music? Theories of the evolution of musicality have focused mainly on the value of music for specific adaptive contexts such as mate selection, parental care, coalition signaling, and group cohesion. Synthesizing and extending previous proposals, we argue that social bonding is an overarching function that unifies all of these theories, and that musicality enabled social bonding at larger scales than grooming and other bonding mechanisms available in ancestral primate societies. We combine cross-disciplinary evidence from archeology, anthropology, biology, musicology, psychology, and neuroscience into a unified framework that accounts for the biological and cultural evolution of music. We argue that the evolution of musicality involves gene-culture coevolution, through which proto-musical behaviors that initially arose and spread as cultural inventions had feedback effects on biological evolution because of their impact on social bonding. We emphasize the deep links between production, perception, prediction, and social reward arising from repetition, synchronization, and harmonization of rhythms and pitches, and summarize empirical evidence for these links at the levels of brain networks, physiological mechanisms, and behaviors across cultures and across species. Finally, we address potential criticisms and make testable predictions for future research, including neurobiological bases of musicality and relationships between human music, language, animal song, and other domains. The music and social bonding hypothesis provides the most comprehensive theory to date of the biological and cultural evolution of music.

Why do humans make music? Theories of the evolution of musicality have focused mainly on the value of music for specific adaptive contexts such as mate selection, parental care, coalition signaling, and group cohesion. Synthesizing and extending previous proposals, we argue that social bonding is an overarching function that unifies all of these theories, and that musicality enabled social bonding at larger scales than grooming and other bonding mechanisms available in ancestral primate societies. We combine cross-disciplinary evidence from archeology, anthropology, biology, musicology, psychology, and neuroscience into a unified framework that accounts for the biological and cultural evolution of music. We argue that the evolution of musicality involves gene-culture coevolution, through which proto-musical behaviors that initially arose and spread as cultural inventions had feedback effects on biological evolution because of their impact on social bonding. We emphasize the deep links between production, perception, prediction, and social reward arising from repetition, synchronization, and harmonization of rhythms and pitches, and summarize empirical evidence for these links at the levels of brain networks, physiological mechanisms, and behaviors across cultures and across species. Finally, we address potential criticisms and make testable predictions for future research, including neurobiological bases of musicality and relationships between human music, language, animal song, and other domains. The music and social bonding hypothesis provides the most comprehensive theory to date of the biological and cultural evolution of music.