EXAMINING THE NATURE, QUALITY, AND REPRESENTATIONS OF GENDER IN POPULAR CHILDREN’S DIGITAL PICTURE BOOK APPS

In recent years, use of digital technology among young children has increased. As a result, digital apps are continuously produced and are often designed to support children’s learning. While research has progressively focused on the use of multimedia apps, little is known about their nature and quality, specifically that of picture book apps. Further, among the body of research examining gender in children’s literature, knowledge of representation and depiction of gender in digital picture book apps is scarce. Therefore, the purpose of this study was to critically examine popular picture book apps for children on a particular popular platform (iOS) in order to understand their nature, quality, and the ways and the degree to which they represent gender. After examining apps based upon inclusion/exclusion criteria, a final sample of 75 apps were used for analysis. Apps were analyzed for genre, the inclusion of transmedial features and the degree of user interactivity of those features, and components of gender. Findings indicate that despite the prevalence of apps that included most of the transmedial features, these apps were generally average in engaging interactivity and limited in genre categorization. Gender disparity was also found across apps, such as the tendency for masculine characters to be the central character and feminine characters to be portrayed with stereotypicaly feminine physical features. This study has implications for users and developers and suggests a general lack of diverse gender representation and the need for high quality, interactive, and engaging picture book apps for the benefit of young children

Student Recital: Kylie Joiner, Viola

Kylie Joiner is a student of Stacey Migliozzi. This recital is given in partial fulfillment of the requirements for the Bachelor of Music, Music Education degree. Kylie Joiner, viola Michael Russo, cello Marie Bliss, pian

Use of Mid-Upper Arm Circumference by Novel Community Platforms to Detect, Diagnose, and Treat Severe Acute Malnutrition in Children: A Systematic Review.

BACKGROUND: A stubborn persistence of child severe acute malnutrition (SAM) and continued gaps in program coverage have made identifying methods for expanding detection, diagnosis, and treatment of SAM an urgent public health need. There is growing consensus that making mid-upper arm circumference (MUAC) use more widely accessible among caregivers and community health workers (CHWs) is an important next step in further decentralizing SAM care and increasing program coverage, including the ability of CHWs to treat uncomplicated SAM in community settings. METHODS: We conducted a systematic review to summarize published and operational evidence published since 2000 describing the use of MUAC for detection and diagnosis of SAM in children aged 6-59 months by caregivers and CHWs, and of management of uncomplicated SAM by CHWs, all outside of formal health care settings. We screened 1,072 records, selected 43 records for full-text screening, and identified 22 studies that met our eligibility criteria. We extracted data on a number of items, including study design, strengths, and weaknesses; intervention and control; and key findings and operational lessons. We then synthesized the qualitative findings to inform our conclusions. The issue of treating children classified as SAM based on low weight-for-height, rather than MUAC, at household level, is not addressed in this review. FINDINGS: We found evidence that caregivers are able to use MUAC to detect SAM in their children with minimal risk and many potential benefits to early case detection and coverage. We also found evidence that CHWs are able to correctly use MUAC for SAM detection and diagnosis and to provide a high quality of care in the treatment of uncomplicated SAM when training, supervision, and motivation are adequate. However, the number of published research studies was small, their geographic scope was narrow, and most described intensive, small-scale interventions; thus, findings are not currently generalizable to public-sector health care systems. CONCLUSIONS: Scaling up the use of MUAC by caregivers and CHWs to detect SAM in household and community settings is a promising step toward improving the coverage of SAM detection, diagnosis, and treatment. Further research on scalability, applicability across a wider range of contexts, coverage impact, and cost is needed. The primary use of MUAC for SAM detection should also be explored where appropriate