Nevin Manimala

Nutr Health. 2025 Mar 20:2601060251329429. doi: 10.1177/02601060251329429. Online ahead of print.

ABSTRACT

BackgroundMany Americans look to primary care physicians (PCPs) for education on how to lead healthier lives. Understanding the duration of nutrition education necessary for PCPs to produce a behavioral impact may inform physician appointment recommendations.AimTo assess whether the duration of nutrition education given by PCPs correlates with changes in dietary behavior, or secondarily, health status, among patients without complex chronic disease.MethodsPRISMA-ScR guidelines were followed for this scoping review. Inclusion criteria of our review included: PCPs providing nutrition/dietary education, dietary intervention, adult participants, original research, manuscript published in English, study conducted in the U.S., and published 2011-present. Databases searched: PubMed, Cumulative Index to Nursing and Allied Health Literature, and Scopus. Exclusion criteria included: patients experiencing complex chronic health conditions. Data extracted included: study design, description of PCP dietary intervention, length of nutrition education, and general directions of health/behavioral outcomes.ResultsThree reviewed papers studying behavioral interventions that included PCP nutrition education yielded a positive impact on patient outcomes such as dietary behavior and/or weight loss, though only two of the three studies yielded results that achieved statistical significance.ConclusionThere appears to be an important role for nutrition education in the primary care setting. However, our review exposed great need for further research on the specific association between duration of nutrition counseling and resulting changes in dietary and health outcomes.

PMID:40112329 | DOI:10.1177/02601060251329429

Work. 2025 Mar 20:10519815251320260. doi: 10.1177/10519815251320260. Online ahead of print.

ABSTRACT

BackgroundWork-related Musculoskeletal Disorders (WMSDs) are a significant concern in occupational health. However, in South Korea, the implementation of effective ergonomic assessment methods remains limited owing to procedural complexities and a lack of understanding. This highlights the critical need for a comprehensive approach to assess musculoskeletal workload and mitigate WMSDs.ObjectiveThe purpose of this study is to compare the reliability of four work posture assessment methods and to propose a new Musculoskeletal Disorder Assessment Index (MDAI) that is easy to use and can evaluate local work load.MethodsThis study introduced a novel Musculoskeletal Disorder Assessment Index (MDAI) that incorporates posture, force, and repeatability as primary risk factors. The MDAI was compared with established assessment methods using empirical data gathered from a manufacturing facility. Thirty-two tasks encompassing diverse physical activities were evaluated using these methods, and their respective action levels were analyzed.ResultsThe MDAI offered a more comprehensive assessment, effectively capturing local workload variations across different body regions. Statistical analysis revealed significant disparities between the MDAI and the other methods, underscoring the distinct advantages of the MDAI approach in accurately assessing local workload. The MDAI excelled in evaluating tasks involving intricate and diverse local workload factors.ConclusionsThis study contributes to the field of ergonomics by introducing a novel musculoskeletal disorder assessment index that enhances the detailed evaluation of local body region workload. Considering posture, force, and repeatability, the MDAI provides a reliable framework for identifying and addressing the risks associated with musculoskeletal disorders.

PMID:40112327 | DOI:10.1177/10519815251320260

J Back Musculoskelet Rehabil. 2025 Mar 20:10538127251323323. doi: 10.1177/10538127251323323. Online ahead of print.

ABSTRACT

BackgroundPregnancy-related carpal tunnel syndrome (PRCTS) is the most common mononeuropathy during pregnancy.Objectiveto compare the efficacy of ultrasound (US)-guided steroid injection alone versus wiht splinting on symptom severity on PRCTS.MethodsThis retrospective cohort study included 37 pregnant women in their third trimester with PRCTS, treated with ultrasound-guided steroid injection of 4 mg dexamethasone into the median nerve (Group I, n = 15), volar splinting in a neutral position while sleeping and during the day whenever possible for at least ten weeks (Group S, n = 12), or both injection and splinting (Group I + S, n = 10). Patient data were collected from hospital records, and symptoms were assessed using the Boston Carpal Tunnel Symptom Questionnaire (BCTQ), the Douleur Neuropathique 4 (DN4) and the Numeric Rating Scale (NRS). Statistical analyses included Student’s t-test, Mann-Whitney U test, Fisher’s exact test, ANOVA, Kruskal-Wallis test, descriptive analyses, and power analyses.ResultsDuring the first month of intervention, group S had higher BCTQ scores than the other two groups (p < 0.001). In the postpartum period, the order of scores was Group S > Group I > Group I + S (p < 0.001). The effect size was significant with Partial eta squared = 0.369.ConclusionThe combination of splinting and injection seems to be more effective in the short term period. But still, to validate our findings, Additional randomized controlled trials are recommended.

PMID:40112320 | DOI:10.1177/10538127251323323

Obstet Gynecol. 2025 Mar 20. doi: 10.1097/AOG.0000000000005885. Online ahead of print.

ABSTRACT

OBJECTIVE: To evaluate the short-term effectiveness of fractional CO2 laser for the treatment of genitourinary syndrome of menopause.

DATA SOURCES: Systematic review was performed of PubMed, Scopus, Web of Science, Cinhal, MEDLINE, and ClinicalTrials.gov.

METHODS OF STUDY SELECTION: The included studies had to meet the following criteria: 1) The sample consisted exclusively of women diagnosed with genitourinary syndrome of menopause; 2) at least one group in the sample underwent treatment with fractional CO2 laser; 3) the control group received simulated fractional CO2 laser therapy, topical hormonal treatment, or a topical gel lubricant; 4) the studies evaluated outcomes related to sexual function, urinary symptoms, or the quality of the vaginal epithelium; and 5) the study design was a randomized controlled trial. The exclusion criterion specified that participants should not have a history of any type of cancer or prior treatment with a different type of laser.

TABULATION, INTEGRATION, AND RESULTS: Two reviewers independently screened articles for eligibility and extracted data. Difference in mean differences and their 95% CIs were calculated as the between-group difference in means divided by the pooled SD. The I2 statistic was used to determine the degree of heterogeneity. The 11 articles included in the review had a group receiving fractional CO2 laser therapy and a control group receiving simulated fractional CO2 laser, topical hormonal treatment, or topical gel lubricant. The meta-analyses indicated that fractional CO2 laser is effective for improving sexual function through increased sexual desire, arousal, lubrication, orgasms, and sexual satisfaction; reducing pain during sexual activity (standardized mean difference 0.51, P=.021); and improving urinary function by reducing the frequency and magnitude of urinary leakage and frequency of urination (standardized mean difference 0.51, P<.001).

CONCLUSION: Fractional CO2 laser is associated with statistically significant improvements in the short-term treatment of sexual and urinary symptoms but not vaginal epithelium quality. The clinical significance of these changes is unclear.

SYSTEMATIC REVIEW REGISTRATION: PROSPERO, CRD42023435636.

PMID:40112298 | DOI:10.1097/AOG.0000000000005885

J Med Internet Res. 2025 Mar 20;27:e69569. doi: 10.2196/69569.

ABSTRACT

BACKGROUND: The use of geosocial networking apps is linked to increased risky sexual behaviors among men who have sex with men, but their relationship with HIV and other sexually transmitted infections remains inconclusive. Since 2015, the prevalence of app use among men who have sex with men in Shenzhen has surged, highlighting the need for research on their spatiotemporal and behavioral patterns to inform targeted prevention and intervention strategies.

OBJECTIVE: This study aims to investigate the population size, spatiotemporal and behavioral patterns, and mobility of app-using men who have sex with men in Shenzhen using mobile big data. The goal is to inform enhanced and innovative intervention strategies and guide health resource allocation.

METHODS: By leveraging mobile big data application technology, we collected demographic and geographic location data from 3 target apps-Blued (Blued Inc), Jack’d (Online Buddies Inc), and Zank (Zank Group)-over continuous time periods. Spatial autocorrelation (Global Moran I) and hot spot analysis (Getis-Ord Gi) were used to identify the geographic clusters. The Geodetector tool (Chinese Academy of Sciences) was adopted to measure spatially stratified heterogeneity features.

RESULTS: From September 2017 to August 2018, a total of 158,387 males aged 15-69 years in Shenzhen used one of the 3 apps, with the majority (71,318, 45.03%) aged 25-34 years. The app user-to-male ratio was approximately 2.6% among all males aged 15-69 years. The estimated population of app-using men who have sex with men in Shenzhen during this period was 268,817. The geographic distribution of app-using men who have sex with men in Shenzhen was clustered, with hot spots primarily located in central and western Shenzhen, while the distribution of HIV testing and counseling was more concentrated in central-eastern Shenzhen. Approximately 60,202 (38%) app-using men who have sex with men left Shenzhen during the Spring Festival, and 37,756 (62.7%) of them returned after the holiday. The destination distribution showed a relatively centralized flow throughout the country, with the largest mobility within Guangdong province (67.7%), followed by lower mobility to Hunan province (7.9%) and other neighboring provinces (3%-5%), such as Jiangxi, Guangxi, and Hubei Provinces.

CONCLUSIONS: Shenzhen has a large population of men who have sex with men. The variation and inconsistent spatiotemporal distribution of app use and HIV testing and counseling emphasize the need to adapt traditional venue-based prevention and intervention to identified hot spots and to launch outreach initiatives that extend beyond traditional healthcare settings. Given the relatively high internal and interprovincial mobility of app-using men who have sex with men, further smartphone-based behavioral monitoring could provide valuable insights for developing enhanced and innovative HIV prevention and intervention strategies. Moreover, our study demonstrates the potential of mobile big data to address critical research gaps often overlooked by traditional methods.

PMID:40112292 | DOI:10.2196/69569

JMIR AI. 2025 Mar 20;4:e65729. doi: 10.2196/65729.

ABSTRACT

BACKGROUND: Recent advancements in Generative Adversarial Networks and large language models (LLMs) have significantly advanced the synthesis and augmentation of medical data. These and other deep learning-based methods offer promising potential for generating high-quality, realistic datasets crucial for improving machine learning applications in health care, particularly in contexts where data privacy and availability are limiting factors. However, challenges remain in accurately capturing the complex associations inherent in medical datasets.

OBJECTIVE: This study evaluates the effectiveness of various Synthetic Data Generation (SDG) methods in replicating the correlation structures inherent in real medical datasets. In addition, it examines their performance in downstream tasks using Random Forests (RFs) as the benchmark model. To provide a comprehensive analysis, alternative models such as eXtreme Gradient Boosting and Gated Additive Tree Ensembles are also considered. We compare the following SDG approaches: Synthetic Populations in R (synthpop), copula, copulagan, Conditional Tabular Generative Adversarial Network (ctgan), tabular variational autoencoder (tvae), and tabula for LLMs.

METHODS: We evaluated synthetic data generation methods using both real-world and simulated datasets. Simulated data consist of 10 Gaussian variables and one binary target variable with varying correlation structures, generated via Cholesky decomposition. Real-world datasets include the body performance dataset with 13,393 samples for fitness classification, the Wisconsin Breast Cancer dataset with 569 samples for tumor diagnosis, and the diabetes dataset with 768 samples for diabetes prediction. Data quality is evaluated by comparing correlation matrices, the propensity score mean-squared error (pMSE) for general utility, and F₁-scores for downstream tasks as a specific utility metric, using training on synthetic data and testing on real data.

RESULTS: Our simulation study, supplemented with real-world data analyses, shows that the statistical methods copula and synthpop consistently outperform deep learning approaches across various sample sizes and correlation complexities, with synthpop being the most effective. Deep learning methods, including large LLMs, show mixed performance, particularly with smaller datasets or limited training epochs. LLMs often struggle to replicate numerical dependencies effectively. In contrast, methods like tvae with 10,000 epochs perform comparably well. On the body performance dataset, copulagan achieves the best performance in terms of pMSE. The results also highlight that model utility depends more on the relative correlations between features and the target variable than on the absolute magnitude of correlation matrix differences.

CONCLUSIONS: Statistical methods, particularly synthpop, demonstrate superior robustness and utility preservation for synthetic tabular data compared with deep learning approaches. Copula methods show potential but face limitations with integer variables. Deep Learning methods underperform in this context. Overall, these findings underscore the dominance of statistical methods for synthetic data generation for tabular data, while highlighting the niche potential of deep learning approaches for highly complex datasets, provided adequate resources and tuning.

PMID:40112290 | DOI:10.2196/65729

J Med Internet Res. 2025 Mar 20;27:e53399. doi: 10.2196/53399.

ABSTRACT

BACKGROUND: Despite a dramatic increase in the number of people with generalized anxiety disorder (GAD), a substantial number still do not seek help from health professionals, resulting in reduced quality of life. With the growth in popularity of social media platforms, individuals have become more willing to express their emotions through these channels. Therefore, social media data have become valuable for identifying mental health status.

OBJECTIVE: This study investigated the social media posts and behavioral patterns of people with GAD, focusing on language use, emotional expression, topics discussed, and engagement to identify digital markers of GAD, such as anxious patterns and behaviors. These insights could help reveal mental health indicators, aiding in digital intervention development.

METHODS: Data were first collected from Twitter (subsequently rebranded as X) for the GAD and control groups. Several preprocessing steps were performed. Three measurements were defined based on Linguistic Inquiry and Word Count for linguistic analysis. GuidedLDA was also used to identify the themes present in the tweets. Additionally, users’ behaviors were analyzed using Twitter metadata. Finally, we studied the correlation between the GuidedLDA-based themes and users’ behaviors.

RESULTS: The linguistic analysis indicated differences in cognitive style, personal needs, and emotional expressiveness between people with and without GAD. Regarding cognitive style, there were significant differences (P<.001) for all features, such as insight (Cohen d=1.13), causation (Cohen d=1.03), and discrepancy (Cohen d=1.16). Regarding personal needs, there were significant differences (P<.001) in most personal needs categories, such as curiosity (Cohen d=1.05) and communication (Cohen d=0.64). Regarding emotional expressiveness, there were significant differences (P<.001) for most features, including anxiety (Cohen d=0.62), anger (Cohen d=0.72), sadness (Cohen d=0.48), and swear words (Cohen d=2.61). Additionally, topic modeling identified 4 primary themes (ie, symptoms, relationships, life problems, and feelings). We found that all themes were significantly more prevalent for people with GAD than for those without GAD (P<.001), along with significant effect sizes (Cohen d>0.50; P<.001) for most themes. Moreover, studying users’ behaviors, including hashtag participation, volume, interaction pattern, social engagement, and reactive behaviors, revealed some digital markers of GAD, with most behavior-based features, such as the hashtag (Cohen d=0.49) and retweet (Cohen d=0.69) ratios, being statistically significant (P<.001). Furthermore, correlations between the GuidedLDA-based themes and users’ behaviors were also identified.

CONCLUSIONS: Our findings revealed several digital markers of GAD on social media. These findings are significant and could contribute to developing an assessment tool that clinicians could use for the initial diagnosis of GAD or the detection of an early signal of worsening in people with GAD via social media posts. This tool could provide ongoing support and personalized coping strategies. However, one limitation of using social media for mental health assessment is the lack of a demographic representativeness analysis.

PMID:40112289 | DOI:10.2196/53399

JMIR Infodemiology. 2025 Mar 20;5:e56116. doi: 10.2196/56116.

ABSTRACT

BACKGROUND: The advent of the internet has transformed the landscape of health information acquisition and sharing. Reddit has become a hub for such activities, such as the subreddit r/medical_advice, affecting patients’ knowledge and decision-making. While the popularity of these platforms is recognized, research into the interactions and content within these communities remains sparse. Understanding the dynamics of these platforms is crucial for improving online health information quality.

OBJECTIVE: This study aims to quantitatively analyze the subreddit r/medical_advice to characterize the medical questions posed and the demographics of individuals providing answers. Insights into the subreddit’s user engagement, information-seeking behavior, and the quality of shared information will contribute to the existing body of literature on health information seeking in the digital era.

METHODS: A cross-sectional study was conducted, examining all posts and top comments from r/medical_advice since its creation on October 1, 2011. Data were collected on March 2, 2023, from pushhift.io, and the analysis included post and author flairs, scores, and engagement metrics. Statistical analyses were performed using RStudio and GraphPad Prism 9.0.

RESULTS: From October 2011 to March 2023, a total of 201,680 posts and 721,882 comments were analyzed. After excluding autogenerated posts and comments, 194,678 posts and 528,383 comments remained for analysis. A total of 41% (77,529/194,678) of posts had no user flairs, while only 0.1% (108/194,678) of posts were made by verified medical professionals. The average engagement per post was a score of 2 (SD 7.03) and 3.32 (SD 4.89) comments. In period 2, urgent questions and those with level-10 pain reported higher engagement, with significant differences in scores and comments based on flair type (P<.001). Period 3 saw the highest engagement in posts related to pregnancy and the lowest in posts about bones, joints, or ligaments. Media inclusion significantly increased engagement, with video posts receiving the highest interaction (P<.001).

CONCLUSIONS: The study reveals a significant engagement with r/medical_advice, with user interactions influenced by the type of query and the inclusion of visual media. High engagement with posts about pregnancy and urgent medical queries reflects a focused public interest and the subreddit’s role as a preliminary health information resource. The predominance of nonverified medical professionals providing information highlights a shift toward community-based knowledge exchange, though it raises questions about the reliability of the information. Future research should explore cross-platform behaviors and the impact of misinformation on public health. Effective moderation and the involvement of verified medical professionals are recommended to enhance the subreddit’s role as a reliable health information resource.

PMID:40112288 | DOI:10.2196/56116

PLoS One. 2025 Mar 20;20(3):e0320074. doi: 10.1371/journal.pone.0320074. eCollection 2025.

ABSTRACT

INTRODUCTION: Clinical microbiology laboratories are essential for diagnosing and monitoring antimicrobial resistance (AMR). Here, we assessed the systems involved in generating, managing and analyzing blood culture data in these laboratories in an upper-middle-income country.

METHODS: From October 2023 to February 2024, we conducted a survey on the utilization of automated systems and laboratory information management systems (LIMS) for blood culture specimens in 2022 across 127 clinical microbiology laboratories (one each from 127 public referral hospitals) in Thailand. We categorized automated systems for blood culture processing into three steps: incubation, bacterial identification, and antimicrobial susceptibility testing (AST).

RESULTS: Of the 81 laboratories that completed the questionnaires, the median hospital bed count was 450 (range, 150-1,387), and the median number of blood culture bottles processed was 17,351 (range, 2,900-80,330). All laboratories (100%) had an automated blood culture incubation system. Three-quarters of the laboratories (75%, n = 61) had at least one automated system for both bacterial identification and AST, about a quarter (22%, n = 18) had no automated systems for either step, and two laboratories (3%) outsourced both steps. The systems varied and were associated with the hospital level. Many laboratories utilized both automated systems and conventional methods for bacterial identification (n = 54) and AST (n = 61). For daily data management, 71 laboratories (88%) used commercial microbiology LIMS, three (4%) WHONET, three (4%) an in-house database software and four (5%) did not use any software. Many laboratories manually entered data of incubation (73%, n = 59), bacterial identification (27%, n = 22) and AST results (25%, n = 20) from their automated systems into their commercial microbiology LIMS. The most common barrier to data analysis was ‘lack of time’, followed by ‘lack of staff with statistical skills’ and ‘difficulty in using analytical software’.

CONCLUSION: In Thailand, various automated systems for blood culture and LIMS are utilized. However, barriers to data management and analysis are common. These challenges are likely present in other upper-middle-income countries. We propose that guidance and technical support for automated systems, LIMS and data analysis are needed.

PMID:40112277 | DOI:10.1371/journal.pone.0320074

Neurology. 2025 Apr 22;104(8):e213486. doi: 10.1212/WNL.0000000000213486. Epub 2025 Mar 19.

ABSTRACT

BACKGROUND AND OBJECTIVES: Stroke is a leading cause of death and disability in the United States and may result in cognitive impairment and the inability to participate in treatment decisions, attesting to the importance of advance care planning (ACP). Although racial and ethnic differences have been shown for ACP in the general population, little is known about these differences specific to patients with stroke. The aim of this study was to examine the presence of ACP and receipt of life-prolonging care by race and ethnicity among decedents who had suffered a stroke.

METHODS: We used the Health and Retirement Study, a nationally representative longitudinal survey. We conducted a cohort study of decedents who died between 2000 and 2018 using multivariable logistic regression models to explore the association between self-reported ethnicity and race and completion of ACP (including a living will [LW] and durable power of attorney for healthcare [DPOAH]) and receipt of life-prolonging care at end of life, controlling for covariates. Stratified models for each race and ethnicity also were conducted.

RESULTS: This study included 3,491 decedents with a reported history of stroke; 57.4% were women, and the mean age was 81.5 years (SD = 10.2). Decedents who identified as non-Hispanic White had the highest end-of-life planning rates (LW: 57%, DPOAH: 72%, and ACP conversation: 63%) compared with those identifying as non-Hispanic Black (LW: 20%, DPOAH 40%, and ACP conversation: 41%) and Hispanic (LW: 20%, DPOAH: 36%, and ACP conversation: 42%; p < 0.001). The presence of ACP discussions, LW, and DPOAH was associated with lower odds of receiving life-prolonging care at end-of-life among non-Hispanic White decedents (OR = .64, CI = .447-0.904; OR = .30, CI = .206-0.445; OR = .61, CI = .386-0.948) but not among those who identified as Hispanic or non-Hispanic Black.

CONCLUSIONS: Hispanic or non-Hispanic Black decedents with stroke had significantly lower rates of ACP discussions, LWs, and naming a DPOAH compared with those who identified as non-Hispanic White. In addition, ACP activities were inversely associated with receipt of life-prolonging care among non-Hispanic White decedents, but not among those who identified as non-Hispanic Black and Hispanic. Small ethnic/racial subgroup sizes limit the generalizability of this study.

PMID:40112272 | DOI:10.1212/WNL.0000000000213486