Sleep experiences of parents of children 18 years or younger with sickle cell disease during the COVID-19 pandemic: a qualitative study.

STUDY OBJECTIVES: The coronavirus disease pandemic has highlighted disparities in health care. Parents assist in sickle cell disease management in children. Understanding sleep in parents of children who are diagnosed with sickle cell disease is an important facet of disease management. Our objectives were to identify sleep characteristics of parents of children with sickle cell disease age 18 years or younger during the coronavirus disease pandemic, to investigate measures used by parents to achieve restful sleep, and to discuss how sleep may be improved in parents of children diagnosed with sickle cell disease. METHODS: This study conducted 14 face-to-face semistructured interviews with parents of children diagnosed with sickle cell disease. A majority of the interviews (93%) were conducted at a hematology clinic. Qualitative thematic analysis was used to analyze data. RESULTS: All parents reported that their child experienced pain because of sickle cell disease. Most parents (86.7%) reported that their child was diagnosed with sickle cell anemia. Four themes were identified: difficulty obtaining restful sleep during their child's sickle cell crisis, sleep during the coronavirus disease pandemic, factors affecting sleep, and effects of sleep disturbance and deprivation on parental performance. CONCLUSIONS: This research has highlighted some of the difficulties experienced by parents of children who are diagnosed with sickle cell disease and allows for additional insight into the sleep experiences of parents as they attempt to manage their child's disease. CITATION: Osborne JC, Odlum M, Sedrak A. Sleep experiences of parents of children 18 years or younger with sickle cell disease during the COVID-19 pandemic: a qualitative study. J Clin Sleep Med. 2024;20(5):777-782.

All alone: A qualitative study of home health aides' experiences during the COVID-19 pandemic in New York.

BACKGROUND: Despite their integral role, Home Health Aides (HHAs) are largely unrecognized as essential to implementing effective infection prevention and control practices in the home healthcare setting. We sought to understand the infection prevention and control needs and challenges associated with caring for patients during the pandemic from the perspective of HHAs. METHODS: From June to August 2020, data were collected from HHAs in the New York metropolitan area using semi-structured qualitative interviews by telephone; 12 HHAs were interviewed in Spanish. Audio-recorded interviews were transcribed, translated and analyzed using conventional content analysis. RESULTS: In total, 25 HHAs employed by 4 unique home care agencies participated. HHAs had a mean age of 49.8 (± 9.1), 24 (97%) female, 11 (44%) Black, 12 (48%) Hispanic. Three major themes related to the experience of HHA's working during the COVID-19 pandemic emerged: (1) all alone, (2) limited access to information and resources, and (3) dilemmas related to enhanced COVID-19 precautions. Hispanic HHAs with limited English proficiency faced additional difficulties related to communication. CONCLUSIONS: We found that HHA communication with nursing staff, plays a key role in infection control efforts in home care. Efforts to manage COVID-19 in home care should include improving communication between HHAs and nursing staff.

Digital phenotyping of sleep patterns among heterogenous samples of Latinx adults using unsupervised learning.

OBJECTIVE: This study aimed to identify sleep disturbance subtypes ("phenotypes") among Latinx adults based on objective sleep data using a flexible unsupervised machine learning technique. METHODS: This study was an analysis of sleep data from three cross-sectional studies of the Precision in Symptom Self-Management Center at Columbia University. All studies focused on sleep health in Latinx adults at increased risk for sleep disturbance. Data on total sleep time (TST), time in bed (TIB), wake after sleep onset (WASO), sleep efficiency (SE), number of awakenings (NOA) and the mean length of nightly awakenings were collected using wrist-mounted accelerometers. Cluster analysis of the sleep data was conducted using an unsupervised machine learning approach that relies on mixtures of multivariate generalized linear mixed models. RESULTS: The analytic sample included 494 days of data from 118 adults (Ages 19-77). A 3-cluster model provided the best fit based on deviance indices (ie, DΔ∼ -75 and -17 from 1- and 2- to 3-cluster models, respectively) and likelihood ratio (Pdiff âˆ¼ 0.93). Phenotype 1 (n = 64) was associated with greater likelihood of overall adequate SE and less variability in SE and WASO. Phenotype 2 (n = 11) was characterized by higher NOAs, and greater WASO and TIB than the other phenotypes. Phenotype 3 (n = 43) was characterized by greater variability in SE, bed times and awakening times. CONCLUSION: Robust digital data-driven modeling approaches can be useful for detecting sleep phenotypes from heterogenous patient populations, and have implications for designing precision sleep health strategies for management and early detection of sleep problems.

Opioid Use in Adults With Sickle Cell Disease Hospitalized During Vaso-Occlusive Crisis: A Systematic Review.

BACKGROUND: While pain is the hallmark of sickle cell disease (SCD), healthcare personnel are often ill-equipped to adequately treat patients who present in vaso-occlusive crisis (VOC). Although symptom severity varies from individual to individual, SCD is characterized by intervallic pain as a result of oxygen deprivation in tissues and organs. Regardless of pain severity, SCD patients are often viewed as drug seekers by healthcare personnel who have concerns regarding patients' dependence on opioids which may lead to addiction. The objective was to assess the types and amount of opioids used to treat VOC in comparison to Centers for Disease Control opioid prescription guidelines. METHODS: Literature search was conducted using CINAHL, PubMed, the Cochrane Library, Web of Science and hand search. Data were analyzed from 1999 to 2018. Randomized trials, observational, and case studies involved hospitalized adults with SCD who were prescribed opioids to treat VOC. Quality assessment was conducted using Downs and Black checklist. Meta-analysis was not conducted. RESULTS: Five studies were conducted in the USA, Arabia and the Netherlands, and the USA and Canada were included. Participants were treated with either morphine or morphine milligram equivalent (MME). No study used the same method of opioid administration. CONCLUSIONS: Patients with SCD who are hospitalized secondary to VOC mostly received opioids for pain well within the Centers for Disease Control and Prevention prescription guidelines. No uniform method exists. Additional research is warranted.

Health Insurance Coverage Mandates: Colorectal Cancer Screening in the Post-ACA Era.

Building a culture of precision public health requires research that includes health delivery model with innovative systems, health policies, and programs that support this vision. Health insurance mandates are effective mechanisms that many state policymakers use to increase the utilization of preventive health services, such as colorectal cancer screening. This study estimated the effects of health insurance mandate variations on colorectal cancer screening post Affordable Care Act (ACA) era. The study analyzed secondary data from the Behavioral Risk Factor Surveillance System (BRFSS) and the NCI State Cancer Legislative Database (SCLD) from 1997 to 2014. BRFSS data were merged with SCLD data by state ID. The target population was U.S. adults, age 50 to 74, who lived in states where health insurance was mandated or nonmandated before and after the implementation of ACA. Using a difference-in-differences (DD) approach with a time-series analysis, we evaluated the effects of health insurance mandates on colorectal cancer screening status based on U.S. Preventive Services Task Force guidelines. The adjusted average marginal effects from the DD model indicate that health insurance mandates increased the probability of up-to-date screenings versus noncompliance by 2.8% points, suggesting that an estimated 2.37 million additional age-eligible persons would receive a screening with such health insurance mandates. Compliant participants' mean age was 65 years and 57% were women (n = 32,569). Our findings are robust for various model specifications. Health insurance mandates that lower out-of-pocket expenses constitute an effective approach to increase colorectal cancer screenings for the population, as a whole. PREVENTION RELEVANCE: The value added includes future health care reforms that increase access to preventive services, such as CRC screening, are likely with lower out-of-pocket costs and will increase the number of people who are considered "up-to-date". Such policies have been used historically to improve health outcomes, and they are currently being used as public health strategies to increase access to preventive health services in an effort to improve the nation's health.

The powder keg: Lessons learned about clinical staff preparedness during the early phase of the COVID-19 pandemic.

BACKGROUND: Little is known about clinical staff's perspectives on preparedness for a pandemic. The purpose of this study was to obtain various clinical staff perspectives about preparedness to meet the demands for care during the early phase of the SARS-CoV-2 (COVID-19) pandemic. METHODS: We conducted a qualitative study using semistructured in-person interviews from March 2020 to April 2020 at a large tertiary academic urban hospital center. Interview guides were informed by the Resilience Framework for Public Health Emergency Preparedness and analyzed using a directed content analysis approach. RESULTS: Fifty-five clinical staff participated in the study. Three themes emerged from the data (1) Risk assessment and planning: "The powder keg," (2) Innovative evolution of roles and responsibilities, and (3) Pandemic response and capacity. In the early phases of the pandemic, participants reported varying levels of risks for dying. However, most participants adapted to practice changes and became innovative in their roles over time. Hierarchies were less relevant during care delivery, whereas team collaboration became crucial in managing workforce capacity. DISCUSSION: As the pandemic progressed, staff preparedness evolved through a trial-and-error approach. CONCLUSIONS: The pandemic is evolving as is clinical staff preparedness to meet the demands of a pandemic. In order to get a grasp on the crisis, clinical staff relied on each other and resorted to new workarounds.

Trends in Poor Health Indicators Among Black and Hispanic Middle-aged and Older Adults in the United States, 1999-2018.

Importance: Adults who belong to racial/ethnic minority groups are more likely than White adults to receive a diagnosis of chronic disease in the United States. Objective: To evaluate which health indicators have improved or become worse among Black and Hispanic middle-aged and older adults since the Minority Health and Health Disparities Research and Education Act of 2000. Design, Setting, and Participants: In this repeated cross-sectional study, a total of 4 856 326 records were extracted from the Behavioral Risk Factor Surveillance System from January 1999 through December 2018 of persons who self-identified as Black (non-Hispanic), Hispanic (non-White), or White and who were 45 years or older. Exposure: The 1999 legislation to reduce racial/ethnic health disparities. Main Outcomes and Measures: Poor health indicators and disparities including major chronic diseases, physical inactivity, uninsured status, and overall poor health. Results: Among the 4 856 326 participants (2 958 041 [60.9%] women; mean [SD] age, 60.4 [11.8] years), Black adults showed an overall decrease indicating improvement in uninsured status (ß = -0.40%; P < .001) and physical inactivity (ß = -0.29%; P < .001), while they showed an overall increase indicating deterioration in hypertension (ß = 0.88%; P < .001), diabetes (ß = 0.52%; P < .001), asthma (ß = 0.25%; P < .001), and stroke (ß = 0.15%; P < .001) during the last 20 years. The Black-White gap (ie, the change in ß between groups) showed improvement (2 trend lines converging) in uninsured status (-0.20%; P < .001) and physical inactivity (-0.29%; P < .001), while the Black-White gap worsened (2 trend lines diverging) in diabetes (0.14%; P < .001), hypertension (0.15%; P < .001), coronary heart disease (0.07%; P < .001), stroke (0.07%; P < .001), and asthma (0.11%; P < .001). Hispanic adults showed improvement in physical inactivity (ß = -0.28%; P = .02) and perceived poor health (ß = -0.22%; P = .001), while they showed overall deterioration in hypertension (ß = 0.79%; P < .001) and diabetes (ß = 0.50%; P < .001). The Hispanic-White gap showed improvement in coronary heart disease (-0.15%; P < .001), stroke (-0.04%; P < .001), kidney disease (-0.06%; P < .001), asthma (-0.06%; P = .02), arthritis (-0.26%; P < .001), depression (-0.23%; P < .001), and physical inactivity (-0.10%; P = .001), while the Hispanic-White gap worsened in diabetes (0.15%; P < .001), hypertension (0.05%; P = .03), and uninsured status (0.09%; P < .001). Conclusions and Relevance: This study suggests that Black-White disparities increased in diabetes, hypertension, and asthma, while Hispanic-White disparities remained in diabetes, hypertension, and uninsured status.

Strategies for increasing impact, engagement, and accessibility in HIV prevention programs: suggestions from women in urban high HIV burden counties in the Eastern United States (HPTN 064).

BACKGROUND: Merely having the tools to end HIV is insufficient. Effectively ending the epidemic necessitates addressing barriers that impede engagement in biomedical and behavioral prevention and wide scale implementation and utilization of existing interventions. This qualitative study identifies suggestions for increasing access to, engagement in, and impact of HIV prevention among women living in cities in high HIV burden counties in the eastern US. METHODS: Data analyzed for the current study were collected via a qualitative sub-study within the HIV Prevention Trials Network Study 064 (HPTN 064), a multisite observational cohort study designed to estimate HIV incidence among women residing in communities with elevated HIV prevalence who also reported personal or partner characteristics associated with increased risk of HIV acquisition. Focus group and interview participants in the qualitative sub-study (N = 288) were from four cities in the eastern US. RESULTS: Thematic analyses revealed four themes describing women's most frequently stated ideas for improving prevention efforts: 1) Promote Multilevel Empowerment, 2) Create Engaging Program Content, 3) Build "Market Demand", and 4) Ensure Accessibility. We conducted additional analyses to identify contradictory patterns in the data, which revealed an additional three themes: 1) Address Structural Risk Factors, 2) Increase Engagement via Pleasure Promotion, 3) Expand Awareness of and Access to Prevention Resources. CONCLUSIONS: Findings may be useful for enhancing women's engagement in and uptake of behavioral and biomedical HIV prevention resources, improving policy, and addressing multilevel risk factors. TRIAL REGISTRATION: Clinicaltrials.gov: NCT00995176 , prospectively registered.

Application of Social Network Analysis of COVID-19 Related Tweets Mentioning Cannabis and Opioids to Gain Insights for Drug Abuse Research.

We applied social network analysis (SNA) to Tweets mentioning cannabis or opioid-related terms to publicly available COVID-19 related Tweets collected from Jan 21st to May 3rd, 2020 (n= 2,558,474 Tweets). We randomly extracted 16,154 Tweets mentioning cannabis and 4,670 Tweets mentioning opioids from the COVID-19 Tweet corpora for our analysis. The cannabis related Tweets created by 6,144 users were disseminated to 280,042,783 users and retweeted 11 times the number of original messages while opioid-related Tweets created by 3,412 users were disseminated to smaller number of users. The opioids Twitter network showed more cohesive online group activities and a cleaner online environment with less disinformation. The cannabis Twitter network showed a less desirable online environment with more disinformation (false information to mislead the public) and stakeholders lacking strong science knowledge. Application of SNA to Tweets provides insights for future online-based drug abuse research during the outbreak.

Application of Topic Modeling to Tweets as the Foundation for Health Disparity Research for COVID-19.

We randomly extracted publicly available Tweets mentioning COVID-19 related terms (n=2,558,474 Tweets) from Tweet corpora collected daily using an API from Jan 21st to May 3rd, 2020. We applied a clustering algorithm to publicly available Tweets authored by African Americans (n=1,763) to detect topics and sentiment applying natural language processing (NLP). We visualized fifteen topics (four themes) using network diagrams (Newman modularity 0.74). Compared to the COVID-19 related Tweets authored by others, positive sentiments, cohesively encouraging online discussions (e.g., Black strong 27.1%, growing up Blacks 22.8%, support Black business 17.0%, how to build resilience 7.8%), and COVID-19 prevention behaviors (e.g., masks 4.7%, encouraging social distancing 9.4%) were uniquely observed in African American Twitter communities. Application of topic modeling techniques to streaming social media Twitter provides the foundation for research team insights regarding information and future virtual based intervention and social media based health disparity research for COVID-19.

Applying Artificial Intelligence to Predict Self-Reported Poor Health Among Black and Hispanic Caregivers with Mild Cognitive Impairment.

We applied artificial intelligence techniques to build correlate models that predict general poor health in a national sample of caregivers with mild cognitive impairment (MCI). Our application of deep learning identified age, duration of caregiving, amount of alcohol intake, weight, myocardial infarction (MI) and frequency of MCI symptoms for Blacks and Hispanics whereas frequency of MCI symptoms, income, weight, coronary heart disease (CHD), age, and use of e-cigarette for the others as the strongest correlates of poor health among 81 variables entered. The application of artificial intelligence efficiently provided intervention strategies for Black and Hispanic caregivers with MCI.

Alcohol Use and Ethnicity Independently Predict Antiretroviral Therapy Nonadherence Among Patients Living with HIV/HCV Coinfection.

BACKGROUND: Adherence to antiretroviral therapy (ART) is important to counter synergistic effects of HIV and hepatitis C (HCV) in patients living with coinfection. Predictors of ART nonadherence among patients living with HIV/HCV coinfection are not well established. This knowledge would be advantageous for clinicians and behavioral health specialists who provide care to patients living with HIV/HCV coinfection. OBJECTIVES: The purpose of this study was to assess prevalence and predictors of ART nonadherence in a sample of patients living with HIV/HCV coinfection who were actively in HIV clinical care. METHOD: A sample of patients living with HIV/HCV coinfection who received care at a university-affiliated HIV clinic (n = 137) between January 2013 and July 2017 were included in the study. Computerized patient-reported data or outcomes (PROs) and electronic medical record data of these respective patients were collected and analyzed. Binomial logistic regression was used to examine predictors of ART nonadherence. RESULTS: The prevalence of ART nonadherence was 31%. In multivariate analysis, African American ethnicity (OR = 3.28, CI 1.241-8.653, p = 0.017) and a higher number of alcoholic drinks per drinking day (OR = 1.31, CI 1.054-1.639, p = 0.015) were positively associated with ART nonadherence. CONCLUSIONS: Behavioral health providers are encouraged to incorporate alcohol use reduce interventions in HIV clinical settings to reduce ART nonadherence among patients living with HIV/HCV coinfection. Additionally, public health professionals and researchers, and clinicians are encouraged to use inductive methods to discover why ART nonadherence disproportionately impacts African American patients living with HIV/HCV coinfection and to develop approaches that are sensitive to those respective barriers.

Exploring HIV concern in a population of Dominican American women midlife and older.

BACKGROUND: The feminization and ethnic diversification of HIV infection, has resulted in a call for gender- and culture-specific prevention strategies for at-risk groups including Latinos in the United States. The steadily changing demographic profile of the AIDS epidemic challenges prevention strategies to remain relevant and up-to-date, particularly in populations of women midlife and older where an understanding of risk remains under explored. As the CDC requests country-specific HIV risk profiles for Latino communities in the US, understanding the socio-economic, behavioral and personal risk reasons of HIV risk for older Dominican women is critical for prevention. METHODS: We conducted focus group discussions informed by the Theory of Gender and Power (TGP). The three constructs of the TGP: 1) Affective influences/social norms; 2) Gender-specific norms and. 3) Power and Authority guided the thematic analysis and identified themes that described the socio-cultural and contextual reasons that that contribute to perceptions of HIV risk. RESULTS: Sixty Dominican American women ages 57-73 participated in our focus group discussions. Sexual Division of Labour: 1) Economic Dependence; 2) Financial Need and 3) Education and Empowerment. Sexual Division of Power: 4) HIV Risk and 5) Relationship Dynamics. Cathexis: Affective Influences/Social Norms: 6) HIV/AIDS Knowledge and 7) Prevention and Testing. Importantly, participants were concerned about partner fidelity when visiting the Dominican Republic, as the country accounts for the second highest HIV rates in the Caribbean. CONCLUSIONS: Our results confirm previous findings about perceptions of HIV risk and provide additional insight into aging-related aspects of HIV risk for Latino women midlife and older.

Understanding Comorbidities and Their Contribution to Predictors of Medical Resource Utilization for an Age- and Sex-Matched Patient Population Living With HIV: Cross-Sectional Study.

BACKGROUND: More than 60% of people aging with HIV are observed to have multiple comorbidities, which are attributed to a variety of factors (eg, biological and environmental), with sex differences observed. However, understanding these differences and their contribution to medical resource utilization remains challenging as studies conducted exclusively and predominantly among males do not translate well to females, resulting in inconsistent findings across study cohorts and limiting our knowledge of sex-specific comorbidities. OBJECTIVE: The objective of the study was to provide further insight into aging-related comorbidities, their associated sex-based differences, and their contribution to medical resource utilization, through the analysis of HIV patient data matched by sex. METHODS: International Classification of Disease 9/10 diagnostic codes that comprise the electronic health records of males (N=229) and females (N=229) were categorized by individual characteristics, chronic and mental health conditions, treatment, high-risk behaviors, and infections and the codes were used as predictors of medical resource utilization represented by Charlson comorbidity scores. RESULTS: Significant contributors to high Charlson scores in males were age (beta=2.37; 95% CI 1.45-3.29), longer hospital stay (beta=.046; 95% CI 0.009-0.083), malnutrition (beta=2.96; 95% CI 1.72-4.20), kidney failure (beta=2.23; 95% CI 0.934-3.52), chemotherapy (beta=3.58; 95% CI 2.16-5.002), history of tobacco use (beta=1.40; 95% CI 0.200-2.61), and hepatitis C (beta=1.49; 95% CI 0.181-2.79). Significant contributors to high Charlson scores in females were age (beta=1.37; 95% CI 0.361-2.38), longer hospital stay (beta=.042; 95% CI 0.005-0.078), heart failure (beta=2.41; 95% CI 0.833-3.98), chemotherapy (beta=3.48; 95% CI 1.626-5.33), and substance abuse beta=1.94; 95% CI 0.180, 3.702). CONCLUSIONS: Our findings identified sex-based differences in medical resource utilization. These include kidney failure for men and heart failure for women. Increased prevalence of comorbidities in people living long with HIV has the potential to overburden global health systems. The development of narrower HIV phenotypes and aging-related comorbidity phenotypes with greater clinical validity will support intervention efficacy.

Correlates of Durable Viral Suppression (DVS) Among Criminal Justice-involved (CJI) Black Men Living with HIV in Louisiana.

Durable viral suppression (DVS) is needed to reduce HIV transmission risk and prevent new HIV infections. We examined changes in viral suppression and correlates of DVS among 97 criminal justice-involved (CJI) Black men living with HIV in Louisiana enrolled in a linkage, re-engagement, and retention in care intervention. Most participants (75%) were Black men who have sex with men. Forty-four percent (44%) were virally suppressed at baseline and only 20% had achieved DVS over a 12-month period. Multinomial logistic regression analyses showed that compared with DVS participants, those with no viral suppression (NVS) and some viral suppression (SVS) were more likely to have lived with HIV for a longer period of time and were less likely to be adherent at baseline. Medication adherence was critical for DVS among this sample of CJI Black men living with HIV who represent a high priority population for HIV care and treatment interventions.

How Twitter Can Support the HIV/AIDS Response to Achieve the 2030 Eradication Goal: In-Depth Thematic Analysis of World AIDS Day Tweets.

BACKGROUND: HIV/AIDS is a tremendous public health crisis, with a call for its eradication by 2030. A human rights response through civil society engagement is critical to support and sustain HIV eradication efforts. However, ongoing civil engagement is a challenge. OBJECTIVE: This study aimed to demonstrate the use of Twitter data to assess public sentiment in support of civil society engagement. METHODS: Tweets were collected during World AIDS Days 2014 and 2015. A total of 39,940 unique tweets (>10 billion users) in 2014 and 78,215 unique tweets (>33 billion users) in 2015 were analyzed. Response frequencies were aggregated using natural language processing. Hierarchical rank-2 nonnegative matrix factorization algorithm generated a hierarchy of tweets into binary trees. Tweet hierarchy clusters were thematically organized by the Joint United Nations Programme on HIV/AIDS core action principles and categorized under HIV/AIDS Prevention, Treatment or Care, or Support. RESULTS: Topics tweeted 35 times or more were visualized. Results show a decrease in 2015 in the frequency of tweets associated with the fight to end HIV/AIDS, the recognition of women, and to achieve an AIDS-free generation. Moreover, an increase in tweets was associated with an integrative approach to the HIV/AIDS response. Hierarchical thematic differences in 2015 included no prevention discussion and the recognition of the pandemic's impact and discrimination. In addition, a decrease was observed in motivation to fast track the pandemic's end and combat HIV/AIDS. CONCLUSIONS: The human rights-based response to HIV/AIDS eradication is critical. Findings demonstrate the usefulness of Twitter as a low-cost method to assess public sentiment for enhanced knowledge, increased hope, and revitalized expectations for HIV/AIDS eradication.

Correlates and aetiological factors associated with hedonic well-being among an ageing population of US men and women: secondary data analysis of a national survey.

OBJECTIVE: To understand the gender-specific factors that uniquely contribute to successful ageing in a US population of men and women, 57-85 years of age. This was achieved through the examination of the correlates of subjective well-being defined by health-related quality of life (HRQoL), across several biological and psychosocial determinants of health. DESIGN: Cross-sectional study. SETTING: The National Social Life, Health and Ageing Project (NSHAP), 2010-2011 a representative sample of the US population. PARTICIPANTS: 3377 adults aged 57-85 (1538 men, 1839 women) from the NSHAP. MAIN OUTCOME MEASURES: The biopsychosocial factors of biological/physiological function, symptom status, functional status, general health perceptions and HRQoL happiness. METHOD: HRQoL was measured using the NSHAP wave 2 multistage, stratified area probability sample of US households (n=3377). Variable selection was guided by the Wilson and Cleary model (WCM) that classifies health outcomes at five main levels and characteristics. RESULTS: Our findings indicate differences in biopsychosocial factors comprised in the WCM and their relative importance and unique impact on HRQoL by gender. Women reported significantly lower HRQoL than men (t=3.5, df=3366). The most significant contributors to HRQoL in women were mental health (B=0.31; 0.22, 0.39), loneliness (B=-0.26; -0.35, -0.17), urinary incontinence (B=-0.22; -0.40, -0.05) and support from spouse/partner (B=0.27; 0.10, 0.43) and family B=0.12; 0.03, 0.20). Men indicated mental health (B=0.21; 0.14, 0.29), physical health (B=0.17; 0.10, 0.23), functional difficulties (B=0.38; 0.10, 0.65), loneliness (B=-0.20; -0.26, -0.12), depression (B=-0.36; -0.58, -0.15) and support from friends (B=0.06; 0.10, 0.11) as significant contributors. Those with greater social support had better HRQoL (F=4.22, df=4). Lack of companionship and reliance on spouse/partner were significant HRQoL contributors in both groups. CONCLUSION: Our findings offer insight into ageing, gender and subjective well-being. The results provide an opportunity to identify biopsychosocial factors to inform interventions to support successful ageing.

Applying Deep Learning to Understand Predictors of Tooth Mobility Among Urban Latinos.

We applied deep learning algorithms to build correlate models that predict tooth mobility in a convenience sample of urban Latinos. Our application of deep learning identified age, general health, soda consumption, flossing, financial stress, and years living in the US as the strongest correlates of self-reported tooth mobility among 78 variables entered. The application of deep learning was useful for gaining insights into the most important modifiable and non-modifiable factors predicting tooth mobility, and maybe useful for guiding targeted interventions in urban Latinos.

Machine Learning to Identify Behavioral Determinants of Oral Health in Inner City Older Hispanic Adults.

We applied machine learning techniques to a community-based behavioral dataset to build prediction models to gain insights about minority dental health and population aging as the foundation for future interventions for urban Hispanics. Our application of machine learning techniques identified emotional and systemic factors such as chronic stress and health literacy as the strongest predictors of self-reported dental health among hundreds of possible variables. Application of machine learning algorithms was useful to build prediction models to gain insights about dental health and minority population aging.

Health Information Needs and Health Seeking Behavior During the 2014-2016 Ebola Outbreak: A Twitter Content Analysis.

INTRODUCTION: For effective public communication during major disease outbreaks like the 2014-2016 Ebola epidemic, health information needs of the population must be adequately assessed. Through content analysis of social media data, like tweets, public health information needs can be effectively assessed and in turn provide appropriate health information to address such needs. The aim of the current study was to assess health information needs about Ebola, at distinct epidemic time points, through longitudinal tracking. METHODS: Natural language processing was applied to explore public response to Ebola over time from July 2014 to March 2015. A total 155,647 tweets (unique 68,736, retweet 86,911) mentioning Ebola were analyzed and visualized with infographics. RESULTS: Public fear, frustration, and health information seeking regarding Ebola-related global priorities were observed across time. Our longitudinal content analysis revealed that due to ongoing health information deficiencies, resulting in fear and frustration, social media was at times an impediment and not a vehicle to support health information needs. DISCUSSION: Content analysis of tweets effectively assessed Ebola information needs. Our study also demonstrates the use of Twitter as a method for capturing real-time data to assess ongoing information needs, fear, and frustration over time.