The purpose of this study was to examine the demographic and geographic disparities in the incidence of newborn babies with Neonatal Abstinence Syndrome (NAS) in the United States from 2012 to 2015. Specifically, I examined the prevalence of NAS according to geographic location (i.e. urban versus rural) and race while also controlling for mother’s insurance type, median household income, and trends over time. Additional analyses explored the relationship between NAS and delivery method, birth weight, and neonatal candidiasis that causes sepsis. Understanding the disparities in NAS and birth outcomes during this period (2012-2015) can help better target interventions for combating the health and economic burdens of NAS since maternal opioid use has continued to rise since 2015. Additionally, existing research into geographic disparities in NAS have only been region-specific. This study expands the scope of this literature by considering urban versus rural disparities across the country.
This project explorers the potential reasons for the discrepancies between state responses to the COVID-19 pandemic, with a particular focus on the possibility of a correlation between political ideology and a state’s nonpharmacological intervention policy timing. In addition to outlining the current literature on the preferences of conservative and liberal ideology, examples of both past and present scientific based pandemic responses are described as well. Given the current understanding of the social and economic dimension of conservative and liberal political ideology, it was hypothesized that there may be a positive correlation between conservative ideology and premature action by a state. Data was collected on the current ideological landscape and the daily COVID-19 cases numbers of each state in addition to tracking each state’s policy changes. Two correlation tests were performed to find that there was no significant positive or negative correlation between the two variables.
Methods: The standard NLP process was used for this study in which a gold standard was reached through matched paired annotations of the forum text in brat and a neural network was trained on the content. Following the annotation process, adjudication occurred to increase the inter-annotator agreement. Categories were developed by local physicians to describe the questions and three pilots were run to test the best way to categorize the questions.
Results: The inter-annotator agreement, calculated via F-score, before adjudication for a 0.7 threshold was 0.378 for the annotation activity. After adjudication at a threshold of 0.7, the inter-annotator agreement increased to 0.560. Pilots 1, 2, and 3 of the categorization activity had an inter-annotator agreement of 0.375, 0.5, and 0.966 respectively.
Discussion: The inter-annotator agreement of the annotation activity may have been low initially since the annotators were students who may have not been as invested in the project as necessary to accurately annotate the text. Also, as everyone interprets the text slightly differently, it is possible that that contributed to the differences in the matched pairs’ annotations. The F-score variation for the categorization activity partially had to do with different delivery systems of the instructions and partially with the area of study of the participants. The first pilot did not mandate the use of the original context located in brat and the instructions were provided in the form of a downloadable document. The participants were computer science graduate students. The second pilot also had the instructions delivered via a document, but it was strongly suggested that the context be used to gain an understanding of the questions’ meanings. The participants were also computer science graduate students who upon a discussion of their results after the pilot expressed that they did not have a good understanding of the medical jargon in the posts. The final pilot used a combination of students with and without medical background, required to use the context, and included verbal instructions in combination with the written ones. The combination of these factors increased the F-score significantly. For a full-scale experiment, students with a medical background should be used to categorize the questions.
This study aimed to see how social media influences parents’ decisions to have their child(ren) vaccinated against the yearly influenza season. The literature review outlined the risks of influenza for children, the use of social media, and influenza vaccination rates. A survey was conducted to assess parents’ frequency of social media use, the information they saw about influenza and its vaccine on social media, their concerns about the influenza vaccine, and how social media influenced their decision-making to vaccinate their child(ren) against this virus. Overall, the sample population did not believe that social media platforms influenced their decision to vaccinate their children for the seasonal influenza. However, the data was insufficient to provide meaningful conclusions on whether there was a significant association between social media use and its influence on parental decisions about the influenza vaccine. Furthermore, data about the poor reliability of health information on social media platforms and the importance of the influenza vaccine was found in this study. Limitations of the study included responses from individuals with advanced educational levels and a background in the health sciences. This may have resulted in a pro-vaccine bias that would affect the results. Lastly, due to the small sample size, we only report preliminary findings for this topic. Future research should be conducted using a large and diverse sample to study the association between the use of specific social media platforms and its influence on parental decisions for influenza vaccine uptake.
Despite differences in schooling and clinical experience prior to practice, advanced practice providers often have similar scopes of practice, which raises concerns about the quality of care being provided. In this paper, we explore if prescribing patterns are comparable between provider types by comparing differences in time spent on pharmacological interventions utilizing a simulated healthcare environment. Physicians (MDs and DOs), Nurse Practitioners (NPs), and Physician Assistants (PAs) actively practicing in Family Practice/Medicine or Internal Medicine in the U.S. state license/recognition were recruited at healthcare conferences and simulation centers. Participants were provided 20 minutes to complete the patient consultation on a Standardized Patient (SP) presenting with a chief complaint of a post-hospitalization follow-up for heart failure, fatigue, and some edema. All encounters were recorded and uploaded to be reviewed by undergraduate evaluators, who were responsible for quantifying the amount of time the participants spent on each of the task categories, including pharmacologic interventions. With a total of 46 participants in this study, the average amount of time spent discussing this activity per visit across each provider type was 14.8 seconds for MDs/DOs, 29.2 seconds for NPs, and 38.8 seconds for PAs. The results of this study suggest that PAs (p= 0.0028) spent significantly more time discussing pharmacological interventions and were significantly more likely to discuss pharmacological interventions (p=0.0243) when compared with physicians (MD/DOs). It is important to note that the sample size of PAs was very small (N=9), which could potentially skew the results and not be representative of the population. With limited literature that examines whether time spent discussing pharmacological interventions is comparable across provider types, it is important for more simulated healthcare research to be conducted on this topic.
Background: Recent studies have shown a decline in birth rates in large metropolitan areas (after accounting for population), which can be possibly explained by barriers to reproduction associated with the COVID-19 pandemic and related lockdowns. Objective: This study’s objective was to investigate the impact of the COVID-19 pandemic and related lockdowns on the fertility rates of women in reproductive ages living in Greater Phoenix. Methods: The total number of inpatient births and people in both Maricopa and Pinal Counties during pre-COVID-19 years (2017-2019) were compared with those during the COVID-19 years (2021) among women in reproductive ages (15-49 years). To make age-specific comparisons, women in reproductive years were divided into eight distinct age group categories (15-17, 18-20, and then five year age group categories to age 49) from which age-specific, general, and total fertility rates were calculated. Results: Using a two-sample z-test for difference in proportions, findings revealed that the general fertility rate in Greater Phoenix had significantly declined from 48 to 46 per 1,000 population from the pre-COVID-19 period to COVID-19 period (P<0.001). Two sample z-tests were also used to compare age-specific fertility rates, which revealed a significant decline in the fertility rate in women ages 15-17 (from 8.0/1000 to 5.0/1000) (P<0.001), 18-20 (from 43.0/1000 to 35.0/1000) (P<0.001), and 21-24 (from 79.0/1000 to 68.0/1000) (P<0.001) from the pre-COVID-19 period to COVID-19 period, while no significant change was observed in the fertility rate in women ages 25-49. Conclusions: The observed general fertility decline in Greater Phoenix as a result of the COVID-19 pandemic poses significant implications for further research on barriers to reproduction brought upon by the COVID-19 pandemic and related lockdown measures. Another direction for further research involves possibly continuing this study to include years 2022 and 2023 in the COVID-19 period, as well as calculating age-specific fertility rates by race.
Despite differences in schooling and clinical experience prior to practice, advanced practice providers often have similar scopes of practice, which raises concerns about the quality of care being provided. In this paper, we explore if prescribing patterns are comparable between provider types by comparing differences in time spent on pharmacological interventions utilizing a simulated healthcare environment. Physicians (MDs and DOs), Nurse Practitioners (NPs), and Physician Assistants (PAs) actively practicing in Family Practice/Medicine or Internal Medicine in the U.S. state license/recognition were recruited at healthcare conferences and simulation centers. Participants were provided 20 minutes to complete the patient consultation on a Standardized Patient (SP) presenting with a chief complaint of a post-hospitalization follow-up for heart failure, fatigue, and some edema. All encounters were recorded and uploaded to be reviewed by undergraduate evaluators, who were responsible for quantifying the amount of time the participants spent on each of the task categories, including pharmacologic interventions. With a total of 46 participants in this study, the average amount of time spent discussing this activity per visit across each provider type was 14.8 seconds for MDs/DOs, 29.2 seconds for NPs, and 38.8 seconds for PAs. The results of this study suggest that PAs (p= 0.0028) spent significantly more time discussing pharmacological interventions and were significantly more likely to discuss pharmacological interventions (p=0.0243) when compared with physicians (MD/DOs). It is important to note that the sample size of PAs was very small (N=9), which could potentially skew the results and not be representative of the population. With limited literature that examines whether time spent discussing pharmacological interventions is comparable across provider types, it is important for more simulated healthcare research to be conducted on this topic.