The most commonly used functional status (FS) instruments were examined to determine the validity, reliability, sensitivity, and specificity to change and feasibility in residents in an assisted living facility (ALF). Twenty-six ALF residents were assessed weekly for up to 8 months using six instruments. Group and single-subject analyses were used to examine associations between instruments and acute events. Two were problematic initially (Katz Index of Independence in Activities of Daily Living and hand grip) and were excluded early in the study. Of the remaining instruments, only the Barthel Index and Resident Assessment Instrument had acceptable psychometric profiles. However, these instruments were either not feasible in this environment or did not capture the full range of FS in this population. The current study's findings suggest that instruments commonly used to measure FS may be inadequate for this population and environment. These findings may be used to develop assessment methods for ALF residents that capture both the full range of FS in ALF settings as well as acute and long-term changes in functioning.
Background: Meeting the growing industry demand for Data Science requires cross-disciplinary teams that can translate machine learning research into production-ready code. Software engineering teams value adherence to coding standards as an indication of code readability, maintainability, and developer expertise. However, there are no large-scale empirical studies of coding standards focused specifically on Data Science projects. Aims: This study investigates the extent to which Data Science projects follow code standards. In particular, which standards are followed, which are ignored, and how does this differ to traditional software projects? Method: We compare a corpus of 1048 Open-Source Data Science projects to a reference group of 1099 non-Data Science projects with a similar level of quality and maturity. Results: Data Science projects suffer from a significantly higher rate of functions that use an excessive numbers of parameters and local variables. Data Science projects also follow different variable naming conventions to non-Data Science projects. Conclusions: The differences indicate that Data Science codebases are distinct from traditional software codebases and do not follow traditional software engineering conventions. Our conjecture is that this may be because traditional software engineering conventions are inappropriate in the context of Data Science projects.
CCS CONCEPTS• Software and its engineering → Software libraries and repositories.
Background: Adolescent idiopathic scoliosis (AIS) has evidencebased, nonoperative treatments proven to be effective with early diagnosis and prompt treatment. The purpose of this study was to identify potential disparities in access to nonoperative treatment for AIS. Specifically, we sought to determine the interaction of socioeconomic factors on a major curve magnitude and recommend treatment at the initial presentation. Methods: A retrospective review of AIS patients who underwent surgery at a single tertiary pediatric hospital between January 1, 2013 and December 31, 2018 was conducted. Patients were divided into 2 groups for comparison: patients with public insurance (PUB) and those with private insurance (PRV). Primary variables analyzed were patient race, Area Deprivation Index (ADI), major curve magnitude, and treatment recommendation at the initial presentation. Univariate and multivariate analyses were conducted to identify the predictors of the major curve magnitude at presentation. Results: A total of 341 patients met the inclusion criteria; PUB and PRV groups consisted of 182 (53.4%) and 159 (46.6%) children, respectively. Overall, the major curve magnitude at presentation was significantly higher in PUB compared with PRV patients (50.0°vs. 45.1°; P = 0.004) and higher in Black patients compared to White patients (51.8 vs. 47.0, P = 0.042). Surgery was recommended for 49.7% of the PUB group and 43.7% of the PRV group. A lesser number of PUB patients had curve magnitudes within the range of brace indications ( ≤ 40°) compared to PRV patients (22.5% vs. 35.2%, respectively; P = 0.010). The odds of having an initial major curve magnitude <40 degrees were 67% lower among Black patients with public insurance compared to Black patients with private insurance (OR = 0.33; 95% CI: 0.13-0.83; P = 0.019).
Conclusion:This study demonstrated disparity in access to nonoperative treatment for pediatric scoliosis. Black patients with public insurance were the most at-risk to present with curve magnitudes exceeding brace indications. Future work focused on understanding the reasons for this significant disparity may help to promote more equitable access to effective nonoperative treatment for adolescent idiopathic scoliosis. Level of Evidence: III.
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