Se Hee Min

Introduction: This study extends prior work by identifying multidimensional profiles of co-occurring mental health and cognitive symptoms that better reflect the complexity of aging and identify high-risk subgroups with more severe symptom profiles. Methods: This secondary analysis used Wave II data from the National Social Life, Health, and Aging Project (NSHAP). Latent profile analysis was conducted to identify distinct symptom profiles and examine associated sociodemographic, clinical, and lifestyle characteristics. Results: A three-profile solution of “Mild,” “Moderate,” and “Severe” was identified. These profiles differed significantly across sociodemographic characteristics (e.g., age, gender, education, employment, income, and access to technology), clinical factors (self-rated health and chronic conditions), and lifestyle behaviors (physical activity, alcohol use, sleep quality, and social engagement). Discussion: These findings highlight substantial heterogeneity in mental health and cognitive symptom profiles among older adults and underscore the need for targeted, accessible, and person-centered interventions to support their mental and cognitive well-being.

In the United States, the incidence rate of new HIV diagnoses continues to increase among young men who have sex with men (YMSM). Despite the availability of effective preventive strategies such as pre-exposure prophylaxis (PrEP), the rate of PrEP adherence remains markedly low especially among YMSM. Previous studies have primarily relied on structured surveys with predefined responses to identify barriers to PrEP adherence which may not fully capture the complexities behind the barriers. This is a secondary data analysis of data from a prospective cohort study focusing on YMSM vulnerable to HIV. A total of 581 participants provided free-text responses regarding reasons for discontinuing PrEP, which served as the primary outcome for the analysis. Natural language processing was conducted to identify potential barriers to PreP adherence and to uncover any previously unidentified barriers in this population. A total of nine categories were identified, with the most prevalent being lack of sexual activity (n = 128), followed by issues related to monogamy/partnership/long-term relationship (n = 73), specific insurance or coverage issues (n = 52), medication-related concerns (n = 41), side effects/health concerns (n = 39), forgetfulness/inconvenience associated with the medication regimen (n = 33), limited healthcare access (n = 26), personal reasons (n = 9), and financial insecurity (n = 8). The NLP analysis demonstrated moderate performance via support vector machine, random forest, gradient boost, and random forest (F-score = 0.75). Our study provides critical insights into specific barriers faced by high-risk YMSM, emphasizing the need for development of targeted interventions aimed at these barriers to improve PrEP access and utilization.

With aging, female older adults experience biochemical changes such as drop in their sex hormones and biomarkers and often encounter stress, which can be manifested in psychological symptoms. Previous literature has confirmed that racial/ethnic differences exist in the interactive relationship between sex hormones, biomarkers, and psychological symptoms. Yet, the racial/ethnic differences in their interactive relationship have not yet been examined. This is a secondary data analysis using the cross-sectional data of Wave II (2010–2011) from the National Social Life, Health, and Aging Project (NSHAP), and included 1,228 female older adults without moderate to severe cognitive impairment. Moderated network analysis was conducted with race as a moderator to examine the interactive relationship among sex hormones, biomarkers, and psychological symptoms and to compare the differences between the White and non-White group. The White group had a more positive relationship between total hemoglobin and cognition (edge weight = 0.18; moderated edge weight = 0.22). The non-White group had a positive relationship between progesterone and anxiety (edge weight = 0.05; moderated edge weight = 0.04) and between estradiol and cognition (edge weight = 0.03; moderated edge weight = 0.03), both of which were not present in the White group. We found a small moderated effect of race, and the strength of relationship among sex hormones, biomarkers, and psychological symptoms was different between the White and non-White group. Our study offers important preliminary findings to understand the potential racial/ethnic disparities that exist among sex hormones, biomarkers, and psychological symptoms in female older adults and the need to take an interactive approach.

Background: Daily preferences are a reflection of how adults wish to have their needs and values addressed, contributing to joy and satisfaction in their daily lives. Clinical settings often regard older adults as a uniform group, neglecting the diversity within this population, which results in a shortfall of person-centered care that overlooks their distinct daily care preferences. At the heart of person-centered care lies the imperative to comprehend and integrate these preferences into the care process. Recognizing and addressing gender differences in older adults is critical to customizing care plans, thereby optimizing quality of life and well-being for individuals. This study addresses the need to understand the diverse daily care preferences of adults, particularly among older populations, who represent a growing demographic with unique needs and interests. Objective: This study aims to identify and analyze the key themes and daily care preferences from unstructured adult text narratives with a focus on uncovering gender-specific variations. Methods: This study used 4350 deidentified, unstructured textual data from MyDirectives (MyDirectives, Inc), an interactive online platform. Advanced topic modeling techniques were used to extract meaningful themes, and gender-specific term frequency and distribution were examined to identify gender differences in these elements. Results: The study sample included 2883 women (mean age 63.02, SD 13.69 years) and 1467 men (mean age 67.07, SD 11.73 years). Our analysis identified six major themes: (1) “entertainment” (12.14%, 528/4350), (2) “music” (10.39%, 452/4350), (3) “personal interests and memories” (38.18%, 1661/4350), (4) “intimate relationships” (14.92%, 649/4350), (5) “natural comforts” (16.18%, 704/4350), and (6) “emotional, cultural, and spiritual foundations” (8.18%, 356/4350). Gender differences were evident: women were more likely to express preferences for “personal interests and memories” (40.7% vs 33.3%), “natural comforts” (18.4% vs 11.9%), and “emotional and spiritual foundations” (9.3% vs 6.1%) than men. Men expressed stronger preferences for “entertainment” (18.1% vs 9.1%) and “music” (16.8% vs 7.2%). Common terms across all participants included “dog,” “love,” “friends,” and “book.” Notably, the study revealed significant gender differences in daily care preferences, especially regarding familial relationships and entertainment choices. Conclusions: The findings underscore the importance of recognizing individual daily care preferences in person-centered care, particularly regarding gender. Understanding these preferences is crucial for improving care quality and patient satisfaction, thereby enhancing the overall quality of life for adults receiving care across our health care system.

Previous studies have focused on identifying risk factors for older adults receiving home healthcare services without considering vital signs. This may provide important information on deteriorating health conditions that may lead to hospitalization and/or emergency department (ED) visits. Thus, it is important to understand the relationship between vital signs and hospitalization and/or ED visits and critical vital sign points for mitigating the higher risks of hospitalization and/or ED visits. This secondary data analysis uses cross-sectional data from a large, urban home healthcare organization ( n = 61,615). A generalized additive model was used to understand the nonlinear relationship between each vital sign and hospitalization and/or ED visits through three unadjusted and adjusted models, and to identify a critical vital sign point related to a higher risk of hospitalization and/or ED visits. A significant nonlinear relationship (effective degree of freedom >2.0) was found between systolic, diastolic blood pressure, heart rate, hospitalization, and/or ED visits. The critical inflection point for systolic blood pressure was 120.36 (SE 3.625, p < .001), diastolic blood pressure was 72.00 (SE 3.108, p < .001), and heart rate was 83.24 (SE 1.994, p = .052). Among all vital signs, the risk of hospitalization and/or ED visits sharply increased when an older adult’s heart rate surpassed 83.24 bpm. Our findings reveal that vital signs may serve as a critical indicator of a patient’s clinical condition, especially related to hospitalization and/or ED visit. Clinicians need to be cognizant of these critical thresholds for each vital sign and monitor any deviations from baseline to preempt adverse outcomes.

Introduction: Midlife women in perimenopause and postmenopause experience a complex array of symptoms. However, there is conflicting evidence on how their symptom experiences differ by menopausal stage. Current studies have not examined the interconnected relationship among menopausal symptoms and understood how this relationship may differ based on the menopausal stage. Methods: This is a secondary data analysis using cross-sectional data (visit 5) from the Study of Women’s Health Across the Nation. Network analysis was used to visualize the network structure and to identify key symptoms. Then, a network comparison test was conducted to compare the symptom network properties. Propensity score matching was used to match participants in terms of their covariates. Results: In midlife women in perimenopause, frequent mood change was the key symptom with the highest strength (1.59), closeness (1.27), and expected influence (1.62). In midlife women in postmenopause, anxiety was the key symptom with the highest closeness (0.95) and expected influence (1.48). The symptom networks were not significantly different between the 2 groups in terms of global strength (global strength = 0.01, P = .974), network structure (network structure = 0.10, P = .461), and specific centrality measure (centrality = −0.10, P = .083). While the symptom networks were not invariant, the key symptoms were different between the 2 groups. Conclusion: Our study findings indicate a potential need for different symptom management approaches for midlife women in perimenopause and postmenopause. With this new knowledge, clinicians should offer targeted key symptom assessment and management.

Our study was designed to update the HIV Knowledge Questionnaire by incorporating pre-exposure prophylaxis (PrEP) knowledge questions, as previous HIV knowledge tools lack this focus. Four rounds of Delphi surveys were conducted with 47 expert participants, each with extensive HIV-related expertise (mean experience: 18.94 years). Expert participants rated item relevance on a scale of 0–3 and provided feedback. An item was removed if over 70% scored it two or less. The process continued until consensus was reached, defined as 80% of items scoring above two by more than 70% of expert participants, with no new suggestions. The final measure included 31 items covering general HIV knowledge, transmission modes, treatment, risk, and PrEP definitions, types, and dosages. Future research is essential to validate this tool for research and clinical settings, ensuring it accurately measures patients' diverse knowledge levels.

The HIV incidence rate continues to increase among youth, especially among young men who have sex with men (YMSM) and young transgender women (YTW). To date, behavioral intention has often been viewed as the likelihood of engaging in prevention behaviors and emphasized as a key antecedent for condom use, disclosure of serostatus, and PrEP use among people living with HIV. In addition, individuals with different sociodemographic factors may have varying degrees of HIV prevention intention, which is a critical knowledge needed to identify facilitators and barriers to HIV prevention intention. This is a secondary data analysis of baseline data from a randomized controlled trial (RCT) (N = 488). This study aimed to identify distinct, latent classes of HIV prevention intention among youth vulnerable to HIV acquisition and to understand the sociodemographic and contextual factors associated with each latent class. Latent class analysis was conducted to identify meaningful latent classes of youths based on HIV prevention intention. Class 1: “High condomless sex, low serosorting, low PrEP intention,” Class 2: “High condomless sex, high serosorting, low PrEP intention,” Class 3: “Moderate condom use, serosorting, low PrEP intention,” and Class 4: “Moderate condom use, high serosorting, moderate PrEP intention” were identified. Significant differences were found in age, sexual orientation, level of education, current employment status, annual household income, housing/living arrangement, and relationship status. Overall, YMSM and YTW without a recent history of HIV testing or PrEP use may have particularly low intentions for HIV prevention, and therefore may be at higher risk for HIV infection.

Introduction: Older adults are a heterogeneous group, and their care experience preferences are likely to be diverse and individualized. Thus, the aim of this study was to identify categories of older adults’ care experience preferences and to examine similarities and differences across different age groups. Methods: The initial categories of older adults’ care experience preferences were identified through a qualitative review of narrative text (n = 3134) in the ADVault data set. A natural language processing (NLP) algorithm was used to automatically and accurately define older adults’ care experience preference categories. Descriptive statistics were used to examine similarities and differences in care experience preference categories across different age groups. Results: The overall average performance of NLP algorithms was relatively high (average F-score = 0.88; range: 0.77-0.96). Through a qualitative review of 350 randomly selected texts, a total of 11 categories were identified. The most frequent category was music, followed by photographs, entertainment, family/friends, religion-related, atmosphere, flower/plants, pet, bed/bedding, hobby, and other. After applying the best performing NLP algorithm to each category, older adults’ care experience preference categories were music (41.32%), followed by photographs (28.47%), entertainment (13.46%), religion-related (n = 12.69%), pet (12.22%), flower/plants (11.51%), family/friends (8.45%), atmosphere (7.75%), bed/bedding (6.12%), and hobby (5.45%). Young-old and old-old adults had similar care experience preferences with music being the most frequent category while old-old adults had photographs as the most frequent category for their care experience preference. Conclusion: Clinicians must understand the distinct categories of care experience preferences and incorporate them into personalized care planning.

Background: The healthcare industry increasingly values high‐quality and personalized care. Patients with heart failure (HF) receiving home health care (HHC) often experience hospitalizations due to worsening symptoms and comorbidities. Therefore, close symptom monitoring and timely intervention based on risk prediction could help HHC clinicians prevent emergency department (ED) visits and hospitalizations. This study aims to (1) describe important variables associated with a higher risk of ED visits and hospitalizations in HF patients receiving HHC; (2) map data requirements of a clinical decision support (CDS) tool to the exchangeable data standard for integrating a CDS tool into the care of patients with HF; (3) outline a pipeline for developing a real‐time artificial intelligence (AI)‐based CDS tool.Methods: We used patient data from a large HHC organization in the Northeastern US to determine the factors that can predict ED visits and hospitalizations among patients with HF in HHC (9362 patients in 12,223 care episodes). We examined vital signs, HHC visit details (e.g., the purpose of the visit), and clinical note–derived variables. The study identified critical factors that can predict ED visits and hospitalizations and used these findings to suggest a practical CDS tool for nurses. The tool's proposed design includes a system that can analyze data quickly to offer timely advice to healthcare clinicians.Results: Our research showed that the length of time since a patient was admitted to HHC and how recently they have shown symptoms of HF were significant factors predicting an adverse event. Additionally, we found this information from the last few HHC visits before the occurrence of an ED visit or hospitalization were particularly important in the prediction. One hundred percent of clinical demographic profiles from the Outcome and Assessment Information Set variables were mapped to the exchangeable data standard, while natural language processing–driven variables couldn't be mapped due to their nature, as they are generated from unstructured data. The suggested CDS tool alerts nurses about newly emerging or rising risks, helping them make informed decisions.Conclusions: This study discusses the creation of a time‐series risk prediction model and its potential CDS applications within HHC, aiming to enhance patient outcomes, streamline resource utilization, and improve the quality of care for individuals with HF.Clinical Relevance: This study provides a detailed plan for a CDS tool that uses the latest AI technology designed to aid nurses in their day‐to‐day HHC service. Our proposed CDS tool includes an alert system that serves as a guard rail to prevent ED visits and hospitalizations. This tool can potentially improve how nurses make decisions and improve patient outcomes by providing early warnings about ED visits and hospitalizations.