I love being a midwife; it\u27s who I am : A Glaserian Grounded Theory Study of why midwives stay in midwifery

Aims and objectives: To understand why Western Australian (WA) midwives choose to remain in the profession. Background: Midwifery shortages and the inability to retain midwives in the midwifery profession is a global problem. The need for effective midwifery staff retention strategies to be implemented is therefore urgent, as is the need for evidence to inform those strategies. Design: Glaserian grounded theory (GT) methodology was used with constant comparative analysis. Methods: Fourteen midwives currently working clinically area were interviewed about why they remain in the profession. The GT process of constant comparative analysis resulted in an overarching core category emerging. The study is reported in accordance with Tong and associates’ (2007) Consolidated Criteria for Reporting Qualitative Research (COREQ). Results: The core category derived from the data was labelled—“I love being a midwife; it\u27s who I am.” The three major categories that underpin the core category are labelled as follows: “The people I work with make all the difference”; “I want to be ‘with woman’ so I can make a difference”; and “I feel a responsibility to pass on my skills, knowledge and wisdom to the next generation.” Conclusion: It emerged from the data that midwives’ ability to be “with woman” and the difference they feel they make to them, the people they work with and the opportunity to “grow” the next generation together underpin a compelling new middle‐range theory of the phenomenon of interest. Relevance to clinical practice: The theory that emerged and the insights it provides will be of interest to healthcare leaders, who may wish to use it to help develop midwifery workforce policy and practice, and by extension to optimise midwives’ job satisfaction, and facilitate the retention of midwives both locally and across Australia

Neighborhood disparities in stroke and myocardial infarction mortality: a GIS and spatial scan statistics approach

<p>Abstract</p> <p>Background</p> <p>Stroke and myocardial infarction (MI) are serious public health burdens in the US. These burdens vary by geographic location with the highest mortality risks reported in the southeastern US. While these disparities have been investigated at state and county levels, little is known regarding disparities in risk at lower levels of geography, such as neighborhoods. Therefore, the objective of this study was to investigate spatial patterns of stroke and MI mortality risks in the East Tennessee Appalachian Region so as to identify neighborhoods with the highest risks.</p> <p>Methods</p> <p>Stroke and MI mortality data for the period 1999-2007, obtained free of charge upon request from the Tennessee Department of Health, were aggregated to the census tract (neighborhood) level. Mortality risks were age-standardized by the direct method. To adjust for spatial autocorrelation, population heterogeneity, and variance instability, standardized risks were smoothed using Spatial Empirical Bayesian technique. Spatial clusters of high risks were identified using spatial scan statistics, with a discrete Poisson model adjusted for age and using a 5% scanning window. Significance testing was performed using 999 Monte Carlo permutations. Logistic models were used to investigate neighborhood level socioeconomic and demographic predictors of the identified spatial clusters.</p> <p>Results</p> <p>There were 3,824 stroke deaths and 5,018 MI deaths. Neighborhoods with significantly high mortality risks were identified. Annual stroke mortality risks ranged from 0 to 182 per 100,000 population (median: 55.6), while annual MI mortality risks ranged from 0 to 243 per 100,000 population (median: 65.5). Stroke and MI mortality risks exceeded the state risks of 67.5 and 85.5 in 28% and 32% of the neighborhoods, respectively. Six and ten significant (p < 0.001) spatial clusters of high risk of stroke and MI mortality were identified, respectively. Neighborhoods belonging to high risk clusters of stroke and MI mortality tended to have high proportions of the population with low education attainment.</p> <p>Conclusions</p> <p>These methods for identifying disparities in mortality risks across neighborhoods are useful for identifying high risk communities and for guiding population health programs aimed at addressing health disparities and improving population health.</p

Gunnison Wash Map

Color photograph google map image of Gunnison black dot marks where the altercation between Don Salovitch and Sheldon Clark happene

William Billion McCleery\u27s Childhood home

Color photograph House that William Billion McCleery Grew up in with his family at 1954 Jackson Ave, in Ogden, Uta

Gunnison Wash

Color photograph google maps street view image of spot where Don Salovitch and Sheldon Clark Fough

Home where Members of the Utah Gay Liberation Front Lived and Met

Color photograph of house with overgrown yard at 578 3rd Av