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Educating Staff To Empower Parental Involvement While Visiting NICU Through The SENSE Program: A Quality Improvement Project
Full text linkPreterm infants in neonatal intensive care units (NICUs) face significant neurodevelopmental risks due to immature sensory systems and limited exposure to developmentally appropriate sensory input. The Supporting and Enhancing NICU Sensory Experiences (SENSE) program is an evidence-based initiative designed to structure sensory care in the NICU, providing infants with consistent, age-appropriate exposure to tactile, auditory, visual, olfactory, vestibular, and kinesthetic stimulation. This Doctor of Nursing Practice (DNP) quality improvement project aimed to implement the SENSE program through targeted education for NICU staff and evaluate its impact on provider knowledge, confidence, and observed parent engagement in sensory-based care.
A total of 15 NICU professionals, including registered nurses, therapists, and clinical care staff, completed matched pre- and post-intervention surveys. Baseline data revealed that only 13% of staff felt confident guiding parents in sensory-based care, and fewer than 30% reported observing consistent use of all five sensory modalities. Common barriers included lack of time, limited training, and low parental involvement. Following a structured educational session using a slide presentation and digital QR-coded resources, all participants (100%) demonstrated improved knowledge of the SENSE program, with a substantial increase in confidence and implementation. Post-intervention, 80% of staff felt moderately or very confident in guiding parents, and 100% reported observing auditory and tactile stimulation during parent-infant interactions. Observations of olfactory and vestibular input rose from 33% and 27% at baseline to 87% and 73%, respectively.
Staff perceived the training materials as helpful, and 93% agreed their educational needs were met. While time constraints and inconsistent parental presence remained concerns, participants expressed strong interest in ongoing mentorship and additional resources to sustain improvements. The results suggest that integrating structured sensory education significantly enhances staff preparedness and fosters improved developmental support for preterm infants. This project reinforces the importance of consistent, interdisciplinary sensory care in NICU settings and highlights the SENSE program as a valuable tool to guide practice change
The Metadata is LLaVA: Evaluating Generative AI for Digital Records
Full text linkThis presentation shares a pilot study to assess the multimodal AI tool LLaVA (Large Language and Vision Assistant) in generating descriptive metadata for digitized photographs. The study focuses on evaluation methods for AI-generated descriptions utilizing structured rubrics, which will assess the accuracy, bias, usability, and overall effectiveness of the AI tool. The presentation will also cover the ethics and best practices of using AI-generated metadata for sensitive content. Attendees will gain insights into practical methods for critically evaluating AI-generated outputs, equipping them with adaptable, relevant assessment techniques that may be useful in various library workflow settings
Trends in Diabetes Mellitus Mortality in Colombia and Spain (1983–2022): An Age-Period-Cohort Analysis
Full text linkObjective: To compare the effects of age, period, and cohort on DM mortality between Colombia and Spain from 1983 to 2022.
Methods: Analytical observational study using aggregated cross-sectional data from mortality records and population projections of both countries. DM deaths for each age, period, and cohort group were organized into five-year intervals. Age-standardized mortality rates (ASMR) and their 95% confidence intervals (CIs) were calculated. A multiple quasi-Poisson model was applied using the intrinsic estimator method. Adjusted mortality rate ratios (MRR) with 95% CIs for each age, period, and cohort group compared to the overall average rate were estimated.
Results: The annual ASMR in Colombia was 17.5 (95% CI 17.4–17.6), while in Spain it was 9.9 (95% CI 9.8–9.9). Period effects differed between countries. In Colombia, the MRR increased from 1983 to 2007 and then decreased between 2008 and 2017. In Spain, a consistent decline was observed from 1983 to 2017. Both countries showed an increase in MRR from 2018 to 2022. DM mortality rose with age, with the 85+ group showing the highest MRR (Colombia: 18.5; 95% CI 16.9–20.3; Spain: 91.8; 95% CI 51.9–162.2). Older cohorts also had higher MRRs. For the 1913–1917 cohort, MRR was 3.6 (95% CI 3.3–3.9) in Colombia and 4.2 (95% CI 3.1–5.6) in Spain.
Conclusion: Public health actions to reduce DM mortality should ensure healthy aging and continuous management of complications and comorbidities, particularly in older adults. Awareness of health care must be prioritized for younger generations
Continuously Generated Diabetes Type 2 Risk scores with Deep Learning
Full text linkObjective:
(i) To introduce a methodology based on TabTransformers to model Diabetes risk scores that can continuously be updated to better adjust to target populations. Benefits include enhanced accuracy, increased sensitivity to local risk factors, and good response to missing or incomplete data.
(ii) Identify the accuracy and benefits of the methodology in existing datasets.
Methods:
The methodology employs a deep neural network architecture known as TabTransformer, which extends the self-attention mechanism, initially developed for translation and language tasks, to tabular data.
The model is initially pretrained with a portion (60%) of data available from Jackson Hearth Study which is a cross-sectional study that was conducted in a sample population of African Americans (20 to 95 years) with and without diabetes (n=3,098). Selected risk factors associated with diabetes are based on the socioecological model. The model is then validated with 20% of the data, evaluated with ROC methodology, and finally adjusted with the final 20% to evaluate the continuous update capability of the TabTransformer.
Results:
The accuracy of the multi-logistic regression method was around 78% while the artificial deep neural network around 80%.
Conclusion:
The proposed model complements the original multi-logistics regression approach with improved accuracy, extra benefits include the easier way to develop the score, better prediction of local factors, insensitivity to missing data, and online training capabilities. All models are appropriate for the development of apps and integration with IT tools
Cross-Sectional Study Analyzing the Association Between Income Level and the Prevalence of Type 2 Diabetes
Full text linkThis abstract summarizes a cross-sectional study that examines how income, education, and race/ethnicity influence the prevalence of type 2 diabetes among U.S. adults. The study found that higher income is significantly associated with a lower likelihood of being diagnosed with diabetes. These findings demonstrate the impact of socioeconomic factors on diabetes with a need for targeted prevention strategies
Association Between Sleep Duration and Cognitive Difficulties in Older Adults: A Cross-Sectional Analysis of the 2020 NHIS
Full text linkSession 2: Bridging Sectors for Health: Building Multisectoral Collaborations to Tackle Chronic Diseases
No full textGhost Guns, Branded Violence: New Trends in the Weapons Seizures Markings
Full text linkThe enduring proliferation of illicit Small Arms and Light Weapons (SALW) remains a critical factor in the security and stability challenges facing Latin America. These armaments fuel organized crime, exacerbate violence, and empower non-state armed actors, thereby undermining governance and public safety. The foundational analysis presented by Andrei Serbin Pont and Alex Miller in the Small Arms and Light Weapons Black Markets in Latin America story map established a comprehensive framework for understanding these dynamics (Serbin Pont & Miller, 2022). This report builds upon that essential work, leveraging a new database of open-source seizure incidents to provide a current and granular update on the state of the illicit arms market.
The data analyzed, derived from police operations and journalistic reports compiled in the SALW dashboard from Brazil, Argentina, Panama, and Guatemala, reveals a market that is not only robust but also increasingly sophisticated and adaptive. A rigorous examination of the new dataset uncovers two significant phenomena that represent an evolution in the illicit arms trade. First, there is a proliferation of fake Colt markings on assault rifles. Second, the presence of other specific markings such as the Punisher skull, on seized firearms introduces another layer of analysis, indicating that weapons are not merely tools of violence but are also powerful symbols of criminal identity and ideology.https://digitalcommons.fiu.edu/jgi_research/1087/thumbnail.jp
Building Reflexive Capacity for the Developing Specialized Literacy Professional through Praxis: Graduate Level Course-Based Assessments as Change Agents
Full text linkThis paper shares findings from a qualitative content analysis of twenty-three literacy specialist candidates\u27 (N=23) textual descriptions of transformative changes made to their pedagogical beliefs about reading/literacy theory and models after engaging in praxis. We found engaging in praxis or reflective practices resulted in awareness of critical incidents or critical realizations that validated and challenged their beliefs of literacy pedagogy, and student learning, as well as impacted their decision-making. We confirmed that when intentionally and meaningfully built into an assessment, critical pedagogy theory (specifically praxis) is a strong tool for both the professor and the literacy specialist candidate