Racial/ethnic disparities in sleep health among adolescents in South Korea: The role of substance use behaviours.

AIM: To examine the relationship between racial/ethnic disparities and substance use behaviours (alcohol and tobacco use) and their impact on the sleep health of South Korean adolescents. DESIGN: Secondary analysis of cross-sectional study data from the 2021 Korea Youth Risk Behaviour Web-based Survey dataset. METHODS: Given that Korean society has historically linked its racial/ethnic identity to a shared bloodline, we categorized 2644 adolescents from the Korea Youth Risk Behaviour Web-based Survey based on their racial/ethnic status, determined by their parents' birthplaces. Using multiple linear regression, we investigated whether the impact of racial/ethnic disparities on sleep health (sleep duration, debt, and timing) varies depending on substance use behaviours (alcohol and tobacco use) after controlling for age, sex, household economic status, depressed mood, suicidal ideation, perceived excessive stress, and anxiety level. RESULTS: Despite no statistical differences in sleep health and the prevalence of substance use between racial/ethnic groups, racial/ethnic minority adolescents experienced greater sleep debt than racial/ethnic majority adolescents when consuming alcohol. Moreover, racial/ethnic minority adolescents were more likely to report psychosocial distress and had lower parental education level. CONCLUSION: Racial/ethnic minority adolescents were more vulnerable to the detrimental effects of alcohol use on sleep health compared to racial/ethnic majority adolescents. This heightened vulnerability may be attributed to the more pronounced psychosocial challenges and the lower socioeconomic status of parents in the racial/ethnic minority group. IMPACT: Racial/ethnic disparities are concerning in South Korea, particularly since the negative effects of substance use on sleep health are intensified among racial/ethnic minority adolescents. Nurses and other healthcare providers should recognize the importance of addressing the social disadvantages linked to racial/ethnic disparities. Beyond just advocating for the cessation of substance use, it is crucial to address these underlying issues to reduce sleep disparities among South Korean adolescents. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.

Identifying oncology caregivers' pretreatment educational and emotional needs to inform future virtual reality educational interventions.

PURPOSE: To identify oncology caregivers' unmet educational needs for the development of a virtual reality experience. METHODS: A qualitative descriptive methodology was used; data were collected via online surveys. RESULTS: Eighteen participants said their educational experiences were overwhelming and emotionally exhausting. They suggested a need to deliver educational information through different modalities and provide more clinician-based resources and support. CONCLUSION: This study identified opportunities to complement traditional pretreatment education tailored to the caregivers' needs and experiences, such as specific procedural information and emotional management while being a caregiver. Creating virtual reality experiences exclusively for oncology caregivers is a novel nurse-led approach that is currently not in existence.

Examining the Supports and Advice That Women With Intimate Partner Violence Experience Received in Online Health Communities: Text Mining Approach.

BACKGROUND: Intimate partner violence (IPV) is an underreported public health crisis primarily affecting women associated with severe health conditions and can lead to a high rate of homicide. Owing to the COVID-19 pandemic, more women with IPV experiences visited online health communities (OHCs) to seek help because of anonymity. However, little is known regarding whether their help requests were answered and whether the information provided was delivered in an appropriate manner. To understand the help-seeking information sought and given in OHCs, extraction of postings and linguistic features could be helpful to develop automated models to improve future help-seeking experiences. OBJECTIVE: The objective of this study was to examine the types and patterns (ie, communication styles) of the advice offered by OHC members and whether the information received from women matched their expressed needs in their initial postings. METHODS: We examined data from Reddit using data from subreddit community r/domesticviolence posts from November 14, 2020, through November 14, 2021, during the COVID-19 pandemic. We included posts from women aged ≥18 years who self-identified or described experiencing IPV and requested advice or help in this subreddit community. Posts from nonabused women and women aged <18 years, non-English posts, good news announcements, gratitude posts without any advice seeking, and posts related to advertisements were excluded. We developed a codebook and annotated the postings in an iterative manner. Initial posts were also quantified using Linguistic Inquiry and Word Count to categorize linguistic and posting features. Postings were then classified into 2 categories (ie, matched needs and unmatched needs) according to the types of help sought and received in OHCs to capture the help-seeking result. Nonparametric statistical analysis (ie, 2-tailed t test or Mann-Whitney U test) was used to compare the linguistic and posting features between matched and unmatched needs. RESULTS: Overall, 250 postings were included, and 200 (80%) posting response comments matched with the type of help requested in initial postings, with legal advice and IPV knowledge achieving the highest matching rate. Overall, 17 linguistic or posting features were found to be significantly different between the 2 groups (ie, matched help and unmatched help). Positive title sentiment and linguistic features in postings containing health and wellness wordings were associated with unmatched needs postings, whereas the other 14 features were associated with postings with matched needs. CONCLUSIONS: OHCs can extract the linguistic and posting features to understand the help-seeking result among women with IPV experiences. Features identified in this corpus reflected the differences found between the 2 groups. This is the first study that leveraged Linguistic Inquiry and Word Count to shed light on generating predictive features from unstructured text in OHCs, which could guide future algorithm development to detect help-seeking results within OHCs effectively.

Factors Influencing the Health Care Utilization Among People With Depression and/or Anxiety Symptoms.

BACKGROUND: This analysis aimed to examine the factors predictive of service utilization among patients with anxiety and/or depression. Quick and appropriate treatment for anxiety and depression can reduce disease burden and improve social functioning. Currently, less than half of the population with comorbid anxiety and depression receives the recommended treatment. AIMS: This analysis aims to identify factors predictive of utilizing mental health treatment for those with anxiety and/or depression by analyzing intrinsic, patient-centered factors. METHOD: This study is a cross-sectional cohort analysis using National Health Interview Survey (NHIS) 2019 data. The sample size is 7,156 adults aged 18 to 64 with family incomes ≤100% of the federal poverty level. We used multivariate logistic regression analysis to identify factors predictive of care utilization in this population. Variables of interest include scores on Patient Health Questionnaire-8 (PHQ-8) and Generalized Anxiety Disorder-7 (GAD-7), service utilization, level of social functioning, having a usual source for care, and previous mental health care utilization. Additional covariates were age, gender, race, country of origin, education, marital status, and insurance coverage. RESULTS: Twenty-one percent of respondents reported using mental health services. Factors predictive of care utilization were older age, female gender, limited social functioning, having a usual source of care, and insurance coverage. CONCLUSION: There are significant barriers to receiving quick and appropriate care for anxiety and/or depression. Strategies should focus on reducing barriers for young adults, men, and the uninsured/underinsured. Strategies for integrating mental health services into primary care could increase the percentage of people with anxiety and/or depression who receive services.

A Study on the Prediction of Cancer Using Whole-Genome Data and Deep Learning.

The number of patients diagnosed with cancer continues to increasingly rise, and has nearly doubled in 20 years. Therefore, predicting cancer occurrence has a significant impact on reducing medical costs, and preventing cancer early can increase survival rates. In the data preprocessing step, since individual genome data are used as input data, they are classified as individual genome data. Subsequently, data embedding is performed in character units, so that it can be used in deep learning. In the deep learning network schema, using preprocessed data, a character-based deep learning network learns the correlation between individual feature data and predicts cancer occurrence. To evaluate the objective reliability of the method proposed in this study, various networks published in other studies were compared and evaluated using the TCGA dataset. As a result of comparing various networks published in other studies using the same data, excellent results were obtained in terms of accuracy, sensitivity, and specificity. Thus, the superiority of the effectiveness of deep learning networks in predicting cancer occurrence using individual whole-genome data was demonstrated. From the results of the confusion matrix, the validity of the model for predicting the cancer using an individual's whole-genome data and the deep learning proposed in this study was proven. In addition, the AUC, which is the area under the ROC curve, which judges the efficiency of diagnosis as a performance evaluation index of the model, was found to be 90% or more, good classification results were derived. The objectives of this study were to use individual genome data for 12 cancers as input data to analyze the whole genome pattern, and to not separately use reference genome sequence data of normal individuals. In addition, several mutation types, including SNV, DEL, and INS, were applied.

Priorities to improve cancer caregiving: report of a caregiver stakeholder workshop.

PURPOSE: Caregivers of people with cancer represent a large, overburdened, and under-recognized part of the cancer care workforce. Research efforts to address the unmet needs of these caregivers are expanding with studies focused on caregivers' skill sets, physical and psychological health, and integration into healthcare delivery. As this field of research continues to expand, integrating caregivers' input is vital to studies to ensure that research aligns with their experiences. METHODS: This is a focus group study of 15 cancer caregivers conducted during a cancer caregiving workshop at the University of Pittsburgh in February 2020. During the workshop, caregivers reviewed, critiqued, and proposed priorities to support caregivers of adults with cancer. We used a multistage consensus building approach to identify priority areas of research and clinical practice to address caregivers' experiences and needs. We used descriptive content analysis to summarize caregivers' priorities. RESULTS: Caregiver-identified priorities included (1) training and information about cancer and treatment, (2) caregiver integration into the patient's healthcare delivery, (3) assistance with navigating the healthcare system, (4) focus on caregiver health and well-being, and (5) policy reform to address caregiver needs. We identified ways in which these priorities can inform cancer caregiving research and practice. CONCLUSION: These recommendations should be considered by researchers, clinicians, cancer center leadership, and policymakers interested in creating caregiver-focused research protocols, interventions, and support systems.

Association between Early Spermarche and Suicide Attempts in Boys: the Korea Youth Risk Behavior Web-based Survey.

BACKGROUND: Puberty is a biologically and psychologically unstable period, and pubertal changes differ by sex. However, most previous studies on pubertal timing and suicide have focused on girls. This study investigated the association between early spermarche and suicide attempts in boys. METHODS: We analyzed a nationally representative sample of Korean adolescents (The Korea Youth Risk Behavior Web-Based Survey, KYRBS) that included approximately 35,000 boys annually from 2011 to 2015. Pubertal timing in boys was defined by spermarche. Complex sampling logistic regression analyses were performed to evaluate the odds ratios (ORs) for suicide attempts between the early and average spermarche groups. RESULTS: The ORs for suicide attempts in boys with early spermarche were significantly higher than those in boys with average spermarche after adjustment for age, perceived stress, depressive symptoms, and suicidal ideation. The ORs from 2011 to 2015 were as follows: 1.782 (P < 0.001), 1.490 (P = 0.002), 1.693 (P < 0.001), 1.541 (P = 0.001), and 1.393 (1.024-1.895; P = 0.035), respectively. CONCLUSION: These findings suggest that early pubertal timing is a risk factor for suicide attempts in Korean boys after adjustment for depressive symptoms, perceived stress, and suicidal ideation, which have been previously reported as risk factors for suicide attempts. Therefore, careful attention should be paid to the prevention of suicide in boys who experience early spermarche in Korea.

The Mediating Effect of Depressive Symptoms on the Relationship between Adverse Childhood Experiences and Problematic Internet Use in Children and Adolescents.

The purpose of this study was to evaluate the mediating effect of depressive symptoms on the relationship between adverse childhood experiences (ACEs) and problematic internet use. The study participants were 180 students between the ages of 9 and 18 years. Path analysis was performed to measure the relationships among ACEs, depressive symptoms and problematic internet use. ACEs significantly affected depressive symptoms (standardized regression weight, 0.36; P < 0.01), and depressive symptoms also affected problematic internet use (standardized regression weight, 0.40; P < 0.01). We found that depressive symptoms had a significant mediating effect on the relationship between problematic internet use and ACEs. The management of depressive symptoms would be important to prevent problematic internet use in children and adolescents with ACEs.

Neurofeedback Treatment on Depressive Symptoms and Functional Recovery in Treatment-Resistant Patients with Major Depressive Disorder: an Open-Label Pilot Study.

BACKGROUND: We evaluated the effects of neurofeedback as an augmentation treatment on depressive symptoms and functional recovery in patients with treatment-resistant depression (TRD). METHODS: We included 24 adult patients with TRD and 12 healthy adults. 24 TRD patients were assigned to the neurofeedback augmentation group (n = 12) and the medication-only (treatment as usual [TAU]) group (n = 12). The neurofeedback augmentation group underwent combined therapy comprising medication and 12-24 sessions of neurofeedback training for 12 weeks. To assess the serum levels of brain-derived neurotrophic factor (BDNF) in both groups, pre- and post-treatment blood samples were obtained. Patients were evaluated using the Hamilton Depression Rating Scale (HAM-D), Beck Depression Inventory (BDI), Clinical Global Impression-Severity (CGI-S), 5-level version of European Quality of Life Questionnaire 5-Dimensional Classification (EQ-5D-5L), and Sheehan Disability Scale (SDS) at baseline, and at the 1-, 4-, and 12-week. RESULTS: From baseline to week 12, neurofeedback training reduced mean scores on HAM-D, BDI-II, CGI-S, and SDS, and increased mean EQ-5D-5L tariff score. In the neurofeedback augmentation group, the response and remission rates were 58.3% and 50.0%, respectively, at week 12. Changes in HAM-D, EQ-5D-5L tariff score, and SDS were significantly larger in the neurofeedback group than in the medication-only (TAU) group. No significant difference in BDNF level was found pre- vs. post-treatment in any of the groups. CONCLUSION: Despite the small sample size, these results suggest that neurofeedback treatment may be effective as an augmentation treatment, not only for depressive symptoms, but also for functional recovery, in patients with TRD. TRIAL REGISTRATION: Clinical Research Information Service Identifier: KCT0004183 ClinicalTrials.gov Identifier: NCT04078438.

The Analysis of Electroencephalography Changes Before and After a Single Neurofeedback Alpha/Theta Training Session in University Students.

The underlying mechanisms of alpha/theta neurofeedback training have not been fully determined. Therefore, this study aimed to test the changes in the brain state feedback during the alpha/theta training. Twenty-seven healthy participants were trained during a single session of the alpha/theta protocol, and the resting quantitative electroencephalography (QEEG) was assessed before and after training. QEEG was recorded at eight scalp locations (F3, F4, C3, C4, T3, T4, O1, and O2), and the absolute power, relative power, ratio of sensory-motor rhythm beta (SMR) to theta (RST), ratio of SMR-mid beta to theta (RSMT), ratio of mid beta to theta (RMT), ratio of alpha to high beta (RAHB), and scaling exponent of detrended fluctuation analysis by each band were measured. The results indicated a significant increase of absolute alpha power, especially the slow alpha band, at all electrodes except T3 and T4. Moreover, the relative alpha power, especially the slow alpha band, showed a significant increase at all electrodes. The relative theta power showed a significant decrease at all electrodes, except T3. A significant decrease in relative beta power, relative lower beta power and relative mid beta power was observed at O1. RST (at C4, O1, and O2), RSMT and RMT (at F4, C4, O1 and O2), and RAHB (at all electrodes) showed significant increase. Scaling exponents at all electrodes except T3 showed a significant decrease. These findings indicate that a one-time session of alpha/theta training might have the possibility to enhance both vigilance and concentration, thus stabilizing the overall brain function.

Caregiving Is a Marathon, Not a Road Race: Reenvisioning Caregiver Support Services in Gynecologic Oncology.

OBJECTIVES: As gynecologic cancer care shifts to the outpatient setting, caregivers are instrumental in helping patients navigate the demands of the disease and treatment. Through social media, we aimed to understand the needs of caregivers of patients with gynecologic cancers and support services necessary to meet these needs. METHODS: On January 10, 2018, a monthly Twitter discussion session was hosted by the GYNecologic Cancer Social Media community (handle @GYNCSM) using the hashtag #GYNCSM. Five topics regarding caregiver needs and support were discussed. Basic descriptive statistics, including means and frequencies of tweets, and a content analysis of the tweets were performed. RESULTS: Forty-six participants posted a total of 471 tweets, with 1.725 million impressions. Four main themes of caregiver needs emerged, including accepting help from others, a need to care for themselves as caregivers, increased access to information and resources, and a need for the health care team to communicate with caregivers. Themes relating to barriers to obtaining support services included practical barriers, a lack of awareness, negative emotions, and a need to do it all themselves. Participants suggested that caregiver support programs include convenient resources, caregiver peer support programs, support for the "work" of caregiving, and support to improve the emotional and physical health of the caregiver. CONCLUSIONS: Experts, patients, and caregivers effectively engaged in social media to identify a wide range of needs of caregivers of women with gynecologic cancers. Further research is needed to identify specific support services that could meet the priority needs of a broader network of caregivers.

The Association Between Online Health Information-Seeking Behaviors and Health Behaviors Among Hispanics in New York City: A Community-Based Cross-Sectional Study.

BACKGROUND: Hispanics are the fastest-growing minority group in the United States and they suffer from a disproportionate burden of chronic diseases. Studies have shown that online health information has the potential to affect health behaviors and influence management of chronic disease for a significant proportion of the population, but little research has focused on Hispanics. OBJECTIVE: The specific aim of this descriptive, cross-sectional study was to examine the association between online health information-seeking behaviors and health behaviors (physical activity, fruit and vegetable consumption, alcohol use, and hypertension medication adherence) among Hispanics. METHODS: Data were collected from a convenience sample (N=2680) of Hispanics living in northern Manhattan by bilingual community health workers in a face-to-face interview and analyzed using linear and ordinal logistic regression. Variable selection and statistical analyses were guided by the Integrative Model of eHealth Use. RESULTS: Only 7.38% (198/2680) of the sample reported online health information-seeking behaviors. Levels of moderate physical activity and fruit, vegetable, and alcohol consumption were low. Among individuals taking hypertension medication (n=825), adherence was reported as high by approximately one-third (30.9%, 255/825) of the sample. Controlling for demographic, situational, and literacy variables, online health information-seeking behaviors were significantly associated with fruit (ß=0.35, 95% CI 0.08-0.62, P=.01) and vegetable (ß=0.36, 95% CI 0.06-0.65, P=.02) consumption and physical activity (ß=3.73, 95% CI 1.99-5.46, P<.001), but not alcohol consumption or hypertension medication adherence. In the regression models, literacy factors, which were used as control variables, were associated with 3 health behaviors: social networking site membership (used to measure one dimension of computer literacy) was associated with fruit consumption (ß=0.23, 95% CI 0.05-0.42, P=.02), health literacy was associated with alcohol consumption (ß=0.44, 95% CI 0.24-0.63, P<.001), and hypertension medication adherence (ß=-0.32, 95% CI -0.62 to -0.03, P=.03). Models explained only a small amount of the variance in health behaviors. CONCLUSIONS: Given the promising, although modest, associations between online health information-seeking behaviors and some health behaviors, efforts are needed to improve Hispanics' ability to access and understand health information and to enhance the availability of online health information that is suitable in terms of language, readability level, and cultural relevance.

Online health information seeking behaviors of Hispanics in New York City: a community-based cross-sectional study.

BACKGROUND: The emergence of the Internet has increased access to health information and can facilitate active individual engagement in health care decision making. Hispanics are the fastest-growing minority group in the United States and are also the most underserved in terms of access to online health information. A growing body of literature has examined correlates of online health information seeking behaviors (HISBs), but few studies have included Hispanics. OBJECTIVE: The specific aim of this descriptive, correlational study was to examine factors associated with HISBs of Hispanics. METHODS: The study sample (N=4070) was recruited from five postal zip codes in northern Manhattan for the Washington Heights Inwood Informatics Infrastructure for Comparative Effectiveness Research project. Survey data were collected via interview by bilingual community health workers in a community center, households, and other community settings. Data were analyzed using bivariate analyses and logistic regression. RESULTS: Among individual respondents, online HISBs were significantly associated with higher education (OR 3.03, 95% CI 2.15-4.29, P<.001), worse health status (OR 0.42, 95% CI 0.31-0.57, P<.001), and having no hypertension (OR 0.60, 95% CI 0.43-0.84, P=.003). Online HISBs of other household members were significantly associated with respondent factors: female gender (OR 1.60, 95% CI 1.22-2.10, P=.001), being younger (OR 0.75, 95% CI 0.62-0.90, P=.002), being married (OR 1.36, 95% CI 1.09-1.71, P=.007), having higher education (OR 1.80, 95% CI 1.404-2.316, P<.001), being in worse health (OR 0.59, 95% CI 0.46-0.77, P<.001), and having serious health problems increased the odds of their household members' online HISBs (OR 1.83, 95% CI 1.29-2.60, P=.001). CONCLUSIONS: This large-scale community survey identified factors associated with online HISBs among Hispanics that merit closer examination. To enhance online HISBs among Hispanics, health care providers and policy makers need to understand the cultural context of the Hispanic population. Results of this study can provide a foundation for the development of informatics-based interventions to improve the health of Hispanics in the United States.

A patient with branch retinal vein occlusion accompanied by superior ophthalmic vein thrombosis due to severe superior ophthalmic vein enlargement in a patient with graves ophthalmopathy.

We report a patient with branch retinal vein occlusion (BRVO) accompanied by superior ophthalmic vein (SOV) thrombosis resulting from severe SOV enlargement in a patient with Graves ophthalmopathy (GO). A 78-year-old woman diagnosed with BRVO presented with reduced vision. She had a more than 20-year history of unilateral GO. Fluorescein angiography and spectralis optical coherence tomography revealed BRVO with cystoid macular edema. Approximately 5 months later, she complained of advanced left proptosis. A computed tomography scan at that time revealed dilated SOV with high internal attenuation due to SOV thrombosis of the left orbit. Because of the uncertain onset of SOV thrombosis and minimal signs of acute orbital congestion, we prescribed prophylactic daily aspirin to improve blood flow rather than a heparin-based treatment. In addition, she was treated with lubricants for exposure keratopathy and a dorzolamide/timolol eyedrops to prevent increases in intraocular pressure. This is the first clinical report of BRVO accompanied by SOV thrombosis due to SOV enlargement in chronic severe GO. It should be recognized that SOV thrombosis can lead to an increase in proptosis even in chronic GO.

Harnessing Health Information Technology in Domestic Violence in the United States: A Scoping Review.

Objectives: The following scoping review aims to identify and map the existing evidence for HIT interventions among women with DV experiences in the United States. And provide guidance for future research, and facilitate clinical and technical applications for healthcare professionals. Methods: Five databases, PubMed, EBSCOhost CINAHL, Ovid APA PsycINFO, Scopus and Google Scholar, were searched from date of inception to May 2023. Reviewers extracted classification of the intervention, descriptive details, and intervention outcomes, including physical safety, psychological, and technical outcomes, based on representations in the included studies. Results: A total of 24 studies were included, identifying seven web-based interventions and four types of abuse. A total of five studies reported safety outcomes related to physical health. Three studies reported depression, anxiety, and post-traumatic stress disorder as psychological health outcomes. The effectiveness of technology interventions was assessed in eight studies. Conclusion: Domestic violence is a major public health issue, and research has demonstrated the tremendous potential of health information technology, the use of which can support individuals, families, and communities of domestic violence survivors.

Women with ovarian cancer's information seeking and avoidance behaviors: an interview study.

Objectives: Despite the importance of using information for ovarian cancer (OvCa) disease management and decision-making, some women with OvCa do not actively seek out information. The purpose of this study is to investigate factors that influence information seeking behaviors and information avoidance behaviors and information resources among women with OvCa and their caregivers. Materials and methods: We conducted in-depth interviews with OvCa patients or caregivers of OvCa (n = 20) and employed deductive and inductive coding methodologies for analysis. Results: Our analysis revealed 5 emerging themes associated with active information seeking behavior, 5 themes of passive information acquisition, and 4 themes of information avoidance behavior. Additionally, we identified participants' preferred information sources for OvCa management, such as health organization or government operated resources and web-based social groups. Discussion: To enhance information access, strategies should be developed to motivate people with OvCa to seek rather than avoid information. The study emphasizes the significance of promoting patient-provider communication and leveraging strong social support networks for effective information acquisition. Conclusion: Our findings provide valuable implications for clinical practice and policymaking, emphasizing the need to improve access to information for individuals with OvCa. By addressing the identified factors influencing information seeking behaviors, healthcare professionals and policymakers can better support patients and caregivers in their information-seeking journey, ultimately enhancing disease management and decision-making outcomes.

Harnessing Machine Learning in Tackling Domestic Violence-An Integrative Review.

Domestic violence (DV) is a public health crisis that threatens both the mental and physical health of people. With the unprecedented surge in data available on the internet and electronic health record systems, leveraging machine learning (ML) to detect obscure changes and predict the likelihood of DV from digital text data is a promising area health science research. However, there is a paucity of research discussing and reviewing ML applications in DV research. METHODS: We extracted 3588 articles from four databases. Twenty-two articles met the inclusion criteria. RESULTS: Twelve articles used the supervised ML method, seven articles used the unsupervised ML method, and three articles applied both. Most studies were published in Australia (n = 6) and the United States (n = 4). Data sources included social media, professional notes, national databases, surveys, and newspapers. Random forest (n = 9), support vector machine (n = 8), and naïve Bayes (n = 7) were the top three algorithms, while the most used automatic algorithm for unsupervised ML in DV research was latent Dirichlet allocation (LDA) for topic modeling (n = 2). Eight types of outcomes were identified, while three purposes of ML and challenges were delineated and are discussed. CONCLUSIONS: Leveraging the ML method to tackle DV holds unprecedented potential, especially in classification, prediction, and exploration tasks, and particularly when using social media data. However, adoption challenges, data source issues, and lengthy data preparation times are the main bottlenecks in this context. To overcome those challenges, early ML algorithms have been developed and evaluated on DV clinical data.

Toward Improving Health Literacy in Patient Education Materials with Neural Machine Translation Models.

Health literacy is the central focus of Healthy People 2030, the fifth iteration of the U.S. national goals and objectives. People with low health literacy usually have trouble understanding health information, following post-visit instructions, and using prescriptions, which results in worse health outcomes and serious health disparities. In this study, we propose to leverage natural language processing techniques to improve health literacy in patient education materials by automatically translating illiterate languages in a given sentence. We scraped patient education materials from four online health information websites: MedlinePlus.gov, Drugs.com, Mayoclinic.org and Reddit.com. We trained and tested the state-of-the-art neural machine translation (NMT) models on a silver standard training dataset and a gold standard testing dataset, respectively. The experimental results showed that the Bidirectional Long Short-Term Memory (BiLSTM) NMT model outperformed Bidirectional Encoder Representations from Transformers (BERT)-based NMT models. We also verified the effectiveness of NMT models in translating health illiterate languages by comparing the ratio of health illiterate language in the sentence. The proposed NMT models were able to identify the correct complicated words and simplify into layman language while at the same time, the models suffer from sentence completeness, fluency, readability, and have difficulty in translating certain medical terms.

Spatiotemporal Patterns of Suicide in Korea From 2009 to 2019 Using Geographic Information Systems.

Objective: When analyzing factors related to suicide, it is necessary to consider the regional characteristics of the areas where individuals live in addition to individual factors. This study aimed to investigate the spatiotemporal association between suicide rates and geographic features and the patterns of this association for all administrative areas in South Korea from 2009 to 2019. Methods: The data used in this study were obtained from the National Statistical Office of the Korean Statistical Information Service. For suicide rates, age-standardized mortality index data per 100 000 people were used. All administrative districts from 2009 to 2019 were divided into 229 regions. Emerging hotspot analysis was used for a 3-dimensional analysis to simultaneously evaluate temporal and spatial clusters. Results: In the 229 regions, there were 27 (11.8%) hotspots and 60 (26.2%) cold spots. Hotspot pattern analysis found 2 (0.9%) new spots, 1 (0.4%) persistent spot, 23 (10.0%) sporadic spots, and 1 (0.4%) oscillating spot. Conclusion: This study found geographic differences in the spatiotemporal patterns of suicide rates in South Korea. The utilization of national resources for suicide prevention should be selectively and intensively prioritized in 3 areas that exhibit unique spatiotemporal patterns.

Association Between Depressed Mood Changes and Physical Activity Among Adolescents Post COVID-19 Pandemic.

Objectives: Following the coronavirus disease 2019 (COVID-19) pandemic, adolescents have experienced decreased physical activity and a decline in mental health. This study analyzed the association between changes in depressed mood after the COVID-19 pandemic and physical activity among adolescents. Methods: The analysis was based on the results of the 17th Youth Health Behavior Online Survey conducted in 2021, which included 54848 middle and high school students in South Korea. Information on physical activity included low-intensity physical activity lasting >60 min/day, high-intensity physical activity, and strength training exercises. A logistic regression analysis was performed to evaluate the association between physical activity and changes in depression after the COVID-19 pandemic. Results: After adjusting for sociodemographic characteristics and previous depression, adolescents who performed strength training exercises more than once per week had a 0.95-fold lower risk (odds ratio [OR]=0.948, 95% confidence interval [CI]=0.905-0.994, p= 0.027) of increasing depression after the COVID-19 pandemic, while the risk of decreasing depression increased by 1.22-fold (OR=1.215, 95% CI=1.131-1.305, p<0.001). The results were not significant for low-intensity physical activity for >60 min/day and high-intensity physical activity. Conclusion: Strength-training exercises are significantly associated with the prevention of depression among adolescents following the COVID-19 pandemic.