An Artificial Intelligence-Based Smartphone App for Assessing the Risk of Opioid Misuse in Working Populations Using Synthetic Data: Pilot Development Study.

BACKGROUND: Opioid use disorder (OUD) is an addiction crisis in the United States. As recent as 2019, more than 10 million people have misused or abused prescription opioids, making OUD one of the leading causes of accidental death in the United States. Workforces that are physically demanding and laborious in the transportation, construction and extraction, and health care industries are prime targets for OUD due to high-risk occupational activities. Because of this high prevalence of OUD among working populations in the United States, elevated workers' compensation and health insurance costs, absenteeism, and declined productivity in workplaces have been reported. OBJECTIVE: With the emergence of new smartphone technologies, health interventions can be widely used outside clinical settings via mobile health tools. The major objective of our pilot study was to develop a smartphone app that can track work-related risk factors leading to OUD with a specific focus on high-risk occupational groups. We used synthetic data analyzed by applying a machine learning algorithm to accomplish our objective. METHODS: To make the OUD assessment process more convenient and to motivate potential patients with OUD, we developed a smartphone-based app through a step-by-step process. First, an extensive literature survey was conducted to list a set of critical risk assessment questions that can capture high-risk behaviors leading to OUD. Next, a review panel short-listed 15 questions after careful evaluation with specific emphasis on physically demanding workforces-9 questions had two, 5 questions had five, and 1 question had three response options. Instead of human participant data, synthetic data were used as user responses. Finally, an artificial intelligence algorithm, naive Bayes, was used to predict the OUD risk, trained with the synthetic data collected. RESULTS: The smartphone app we have developed is functional as tested with synthetic data. Using the naive Bayes algorithm on collected synthetic data, we successfully predicted the risk of OUD. This would eventually create a platform to test the functionality of the app further using human participant data. CONCLUSIONS: The use of mobile health techniques, such as our mobile app, is highly promising in predicting and offering mitigation plans for disease detection and prevention. Using a naive Bayes algorithm model along with a representational state transfer (REST) application programming interface and cloud-based data encryption storage, respondents can guarantee their privacy and accuracy in estimating their risk. Our app offers a tailored mitigation strategy for specific workforces (eg, transportation and health care workers) that are most impacted by OUD. Despite the limitations of the study, we have developed a robust methodology and believe that our app has the potential to help reduce the opioid crisis.

Communication strategies to facilitate emergency preparedness for Generation Z and college food pantries: Lessons from the COVID-19 pandemic.

BACKGROUND: There is a paucity of research on college food pantry operations, especially in relation to emergency preparedness and disaster relief. However, there are multiple research studies confirming the efficacy of using social media to communicate with younger adults, especially Generation Z (Gen Z). METHODS: This study examines a college food pantry's social media posts and pantry utilization in a midsize, public university in Texas, prior to and during the COVID-19 pandemic. Collegiate food insecurity was analyzed through the lens of the socioecological model. Social media data during the spring 2019 semester were compared using a two-way ANOVA prior to and following the origination of the COVID-19 pandemic within the state, and pantry utilization over the spring 2019 and fall 2020 semesters was evaluated using a t-test. RESULTS: There were significantly more likes per post on Instagram than other social media outlets, and there were significantly more impressions per post on Twitter as opposed to Facebook, with a trend toward more impressions per posts, after COVID-19. There was no significant difference in food pantry utilization between the fall and spring semester aside from a spike after return following the spring recess, confirmed as Grubb's outlier. Application of the socioecological model emphasized the importance of interdisciplinary collaboration and multitiered interventions during an emergency, including the use of social media. CONCLUSION: This information can help collegiate organizations reach more students through targeted posting on select social media platforms used by their students. Interdisciplinary, inclusive approaches are recommended to reduce food insecurity for Gen Z students.

A Public Safety Compliance Model of Safety Behaviors in the Age of the COVID-19 Pandemic.

The outbreak of COVID-19 has placed a heavy burden on society, threatening the future of the entire world as the pandemic has hit health systems and economic sectors hard. Where time moves fast, continuing curfews and lockdown is impossible. This paper assembles three main safety behaviors, social distancing, wearing a facemask, and hygiene in one model (PSC Triangle) to be practiced by the public. Integrating public safety compliance with these behaviors is the main recommendation to slow the spread of COVID-19. Although some concerns and challenges face these practices, the shifting of public behaviors to be more safety-centered is appropriate and available as an urgent desire exists to return to normal life on the one hand and the medical effort to find effective cure or vaccine that has not yet succeeded on the other hand. Recommendations to enhance public safety compliance are provided.

Zika Virus and the Risk for Renter Households.

Recent research on family income indicates that a lack of economic stability can affect healthy housing. Those with limited resources experience higher rates of inadequate and unstable housing many times forcing them to live in undesirable communities in which there can be several community-level health-related issues. One community-level health-related factor of concern has been the reemergence of Zika virus. Some research has indicated that a higher risk of catching Zika virus may exist in neighborhoods and areas with unhealthy housing. Therefore, this study sought to explore the existence of a relationship between rental housing and the Zika virus. Our findings indicated a significant correlation existed between renter occupied household units and the presence of Zika virus. This finding is notable as it indicates that renters have a higher chance of contracting Zika virus than non-renters. Future research should further examine the demographic and housing situation in other communities reporting cases of the Zika virus.

Parental Guidance Required: How Parents Could Help Reduce the Shortage of Minority Physician Assistants.

Physician assistants (PAs) are essential to the health care system, and there are not nearly enough of them to meet the needs of our ethnically diverse population. Factors contributing to a lack of minorities in PA schools are related to academic performance, commitments outside work/school, and social and economic deprivation. From 2014 to 2016, the Texas Area Health Education Center East worked with the University of Texas Medical Branch at Galveston to implement Physician Assistant Learner Support programming. This program, targeting minority high school students, promoted and educated both students and parents about PA careers with the objective of alleviating one of the main barriers to minority higher education-lack of understanding of educational and career opportunities. This study found that parental knowledge about PA application requirements, PA degree requirements, financial aid, and career prospects at the high school level is essential to securing parental support of student selection of PA careers.

Collaborating to Create Healthier Communities.

The Montgomery County United Way and Sam Houston State University explored existing public health and community-based issues and associated assets and gaps within Montgomery County, Texas, through the integration of quantitative geospatial data, demographic information, and the application of geographical information systems. The intent of the initial results was to use maps to visually compare the magnitude of significant emerging health issues in Montgomery County with other counties across Texas in an effort to better educate and increase the awareness of the general public within Montgomery County. The second objective was to present an example of the visual effect and impact of the overall spatial analysis and mapping process with a focus on a specific community issue that could likely be addressed and potentially solved in a relatively short amount of time. This second and more spatially detailed aspect of the evaluation resulted in the creation of an asset map that presented high concentrations or densities of payday loan services in Montgomery County. Recognizing the potential risks of payday loans, Montgomery County United Way presented the asset maps to the effected community leaders. Upon review, leaders discovered there were dense clusters of payday loan sites in areas with high rates of poverty. Prior to the creation of this aggregated payday loan business location map, an individual in a community typically only saw one, or two at the most, payday loan business during a daily commute. Within a very short period and through a grassroots effort to improve community well-being, there were significant formal and positive changes made by the community.

Improving Primary Care Retention in Medically Underserved Areas: What's a Clinic to Do?

To reduce health professional shortage areas, the National Health Service Corps has attempted to increase the number of primary care providers in underserved communities through scholarships and loan repayment. Program evaluations assessed Loan Repayment Program (LRP) propensity to work in underserved communities. The National Health Service Corps LRPs were asked about preferences for particular retention strategies and which strategies were utilized by their clinical sites. Loan Repayment Programs were asked to rank retention strategies. Loan Repayment Program top choices were competitive salary, 88%; professional development, 70%; knowledgeable/competent support staff, 59%, and professional support, 58%. Loan Repayment Programs were also asked to rank retention strategies provided by their clinical sites: professional development, 74.2%; competitive salary, 71.2%; policies that prohibit abusive behavior, 63.6%, and knowledgeable/competent support staff, 60.6%. Loan Repayment Programs indicated professional support was an important retention element. However, when asked if professional support opportunities were offered, LRP indicated that these were not in the strategies offered by sites.