Tag: nevin manimala

J Med Internet Res. 2025 May 12;27:e65397. doi: 10.2196/65397.

ABSTRACT

BACKGROUND: Domestic violence (DV) is a significant public health concern affecting the physical and mental well-being of numerous women, imposing a substantial health care burden. However, women facing DV often encounter barriers to seeking in-person help due to stigma, shame, and embarrassment. As a result, many survivors of DV turn to online health communities as a safe and anonymous space to share their experiences and seek support. Understanding the information needs of survivors of DV in online health communities through multiclass classification is crucial for providing timely and appropriate support.

OBJECTIVE: The objective was to develop a fine-tuned large language model (LLM) that can provide fast and accurate predictions of the information needs of survivors of DV from their online posts, enabling health care professionals to offer timely and personalized assistance.

METHODS: We collected 294 posts from Reddit subcommunities focused on DV shared by women aged ≥18 years who self-identified as experiencing intimate partner violence. We identified 8 types of information needs: shelters/DV centers/agencies; legal; childbearing; police; DV report procedure/documentation; safety planning; DV knowledge; and communication. Data augmentation was applied using GPT-3.5 to expand our dataset to 2216 samples by generating 1922 additional posts that imitated the existing data. We adopted a progressive training strategy to fine-tune GPT-3.5 for multiclass text classification using 2032 posts. We trained the model on 1 class at a time, monitoring performance closely. When suboptimal results were observed, we generated additional samples of the misclassified ones to give them more attention. We reserved 184 posts for internal testing and 74 for external validation. Model performance was evaluated using accuracy, recall, precision, and F₁-score, along with CIs for each metric.

RESULTS: Using 40 real posts and 144 artificial intelligence-generated posts as the test dataset, our model achieved an F₁-score of 70.49% (95% CI 60.63%-80.35%) for real posts, outperforming the original GPT-3.5 and GPT-4, fine-tuned Llama 2-7B and Llama 3-8B, and long short-term memory. On artificial intelligence-generated posts, our model attained an F₁-score of 84.58% (95% CI 80.38%-88.78%), surpassing all baselines. When tested on an external validation dataset (n=74), the model achieved an F₁-score of 59.67% (95% CI 51.86%-67.49%), outperforming other models. Statistical analysis revealed that our model significantly outperformed the others in F₁-score (P=.047 for real posts; P<.001 for external validation posts). Furthermore, our model was faster, taking 19.108 seconds for predictions versus 1150 seconds for manual assessment.

CONCLUSIONS: Our fine-tuned LLM can accurately and efficiently extract and identify DV-related information needs through multiclass classification from online posts. In addition, we used LLM-based data augmentation techniques to overcome the limitations of a relatively small and imbalanced dataset. By generating timely and accurate predictions, we can empower health care professionals to provide rapid and suitable assistance to survivors of DV.

PMID:40354642 | DOI:10.2196/65397

J Med Internet Res. 2025 May 12;27:e69657. doi: 10.2196/69657.

ABSTRACT

BACKGROUND: College students and young adults (18-25 years) frequently experience poor sleep quality, with insomnia being particularly prevalent among this population. Given the widespread use of digital devices in the modern world, electronic device-based sleep interventions present a promising solution for improving sleep outcomes. However, their effects in this population remain underexplored.

OBJECTIVE: We aimed to synthesize current evidence on the effectiveness of electronic device-based sleep interventions in enhancing sleep outcomes among college students and young adults.

METHODS: In total, 5 electronic databases (PubMed, CINAHL, Cochrane Library, Embase, and Web of Science) were searched to identify randomized controlled trials on digital sleep interventions. Sleep interventions, including cognitive behavioral therapy for insomnia, mindfulness, and sleep education programs delivered via web-based platforms or mobile apps, were evaluated for their effects on sleep quality, sleep parameters, and insomnia severity. Pooled estimates of postintervention and follow-up effects were calculated using Hedges g and 95% CIs under a random-effects model. Heterogeneity was assessed with I² statistics, and moderator and meta-regression analyses were performed to explore sources of heterogeneity. Evidence quality was evaluated using the Grading of Recommendations Assessment, Development, and Evaluations framework.

RESULTS: This study included 13 studies involving 5251 participants. Digital sleep interventions significantly improved sleep quality (Hedges g=-1.25, 95% CI -1.83 to -0.66; I²=97%), sleep efficiency (Hedges g=0.62, 95% CI 0.18-1.05; I²=60%), insomnia severity (Hedges g=-4.08, 95% CI -5.14 to -3.02; I²=99%), dysfunctional beliefs and attitudes about sleep (Hedges g=-1.54, 95% CI -3.33 to -0.99; I²=85%), sleep hygiene (Hedges g=-0.19, 95% CI -0.34 to -0.03; I²=0%), and sleep knowledge (Hedges g=-0.27, 95% CI 0.09-0.45; I²=0%). The follow-up effects were significant for sleep quality (Hedges g=-0.53, 95% CI -0.96 to -0.11; I²=78%) and insomnia severity (Hedges g=-2.65, 95% CI -3.89 to -1.41; I²=99%). Moderator analyses revealed several significant sources of heterogeneity in the meta-analysis examining the effects of digital sleep interventions on sleep outcomes. Variability in sleep quality was influenced by the sleep assessment tool (P<.001), intervention type and duration (P=.001), therapist guidance (P<.001), delivery mode (P=.002), history of insomnia (P<.001), and the use of intention-to-treat analysis (P=.001). Heterogeneity in insomnia severity was primarily attributed to differences in the sleep assessment tool (P<.001), while the effect size on sleep efficiency varied based on intervention duration (P=.02). The evidence quality ranged from moderate to very low certainty across measured outcomes.

CONCLUSIONS: Digital sleep interventions are effective in improving sleep quality and reducing insomnia severity, with moderate effects on dysfunctional beliefs and attitudes about sleep, sleep hygiene, and sleep knowledge. These interventions offer a viable approach to managing sleep problems in college students and young adults.

TRIAL REGISTRATION: PROSPERO CRD42024595126; https://www.crd.york.ac.uk/PROSPERO/view/CRD42024595126.

PMID:40354636 | DOI:10.2196/69657

JMIR Form Res. 2025 May 12;9:e69138. doi: 10.2196/69138.

ABSTRACT

BACKGROUND: The growing prevalence of multiple chronic conditions (MCC) has significant impacts on health care systems and quality of life. Understanding the prevalence of MCC throughout adulthood offers valuable insights into the evolving burden of chronic diseases and provides strategies for more effective health care outcomes.

OBJECTIVE: This study estimated the prevalence and combinations of MCC among adult participants enrolled in the All of Us (AoU) Research Program, especially studying the variations across age categories.

METHODS: We conducted an exploratory analysis using electronic health record (EHR) data from adult participants (N=242,828) in the version 7 Controlled Tier AoU Research Program data release. Data analysis was conducted using Python in a Jupyter notebook environment within the AoU Researcher Workbench. Descriptive statistics included condition frequencies, the number of chronic conditions per participant, and prevalence according to age categories. The presence of a chronic condition was determined by documentation of one or more ICD-10 (International Statistical Classification of Diseases, Tenth Revision) codes for the respective condition. Age categories were established and aligned with diagnosis dates and stages of adulthood (early adulthood: 18-39 years; middle adulthood: 40-49 years; late middle adulthood: 50-64 years; late adulthood: 65-74 years; advanced old age: 75-89 years).

RESULTS: Our findings demonstrated that approximately 76% (n=183,753) of AoU participants were diagnosed with MCC, with over 40% (n=98,885) having 6 or more conditions and prevalence increasing with age (from 33.78% in early adulthood to 68.04% in advanced old age). The most frequently occurring MCC combinations varied by age category. Participants aged 18-39 years primarily presented mental health-related MCC combinations (eg, anxiety and depressive disorders; n=845), whereas those aged 40-64 years frequently had combinations of physical conditions such as fibromyalgia, chronic pain, fatigue, and arthritis (204 in middle adulthood and 457 in late middle adulthood). In late adulthood and advanced old age, hyperlipidemia and hypertension were the most commonly occurring MCC combinations (n=200 and n=59, respectively).

CONCLUSIONS: We report notable prevalence of MCC throughout adulthood and variability in MCC combinations by age category in AoU participants. The significant prevalence of MCC underscores a considerable public health challenge, revealed by distinct condition combinations that shift across different life stages. Early adulthood is characterized predominantly by mental health conditions, transitioning to cardiometabolic and physical health conditions in middle, late, and advanced ages. These findings highlight the need for targeted, innovative care modalities and population health initiatives to address the burden of MCC throughout adulthood.

PMID:40354632 | DOI:10.2196/69138

JMIR Mhealth Uhealth. 2025 May 12;13:e63022. doi: 10.2196/63022.

ABSTRACT

BACKGROUND: Exercise is a primary recommended treatment for knee osteoarthritis (KOA), as it helps alleviate symptoms and improves joint functionality. Personalized exercise programs, tailored to individual patient needs, have demonstrated promising results in maintaining physical fitness and enhancing overall well-being. In recent years, digital health applications have emerged as innovative tools for supervising and facilitating rehabilitation programs. Leveraging computer vision (CV) technology, these applications offer the potential to provide precise feedback and support personalized exercise interventions for patients with KOA in a scalable and accessible manner.

OBJECTIVE: This study aims to evaluate the impact of a CV-graded exercise intervention application over a 6-week period on clinical outcomes in patients with KOA . The outcomes were compared to those achieved through conventional exercise education by videos.

METHODS: A randomized controlled trial was conducted with 60 participants aged 60-80 years, recruited through community administrators between July 2023 and September 2023. Participants were randomly assigned to one of two groups: the graded exercise application group (n=32) and the exercise education brochure group (n=28). The primary outcomes assessed were short-term changes in pain, physical function, and stiffness as measured by the Western Ontario and McMaster Universities Arthritis Index (WOMAC). Secondary outcomes included assessments of participants’ affective state, self-efficacy, quality of life, and user experience.

RESULTS: The study recruited 60 participants, including 26 males and 34 females. Analysis revealed statistically significant improvements in physical function (P=.02) and self-efficacy (P=.04) in the graded exercise application group compared to the exercise education brochure group after the intervention. While improvements in pain and stiffness were observed in both groups, these changes were not statistically significant. In addition, participants in the graded exercise application group reported a positive user experience, highlighting the application’s usability and engagement features as beneficial to their rehabilitation process.

CONCLUSIONS: The findings suggest that the CV-based graded exercise intervention application effectively improves physical function and self-efficacy among patients with KOA . This digital tool demonstrates the potential to enhance the quality and personalization of exercise rehabilitation compared to traditional methods. Future studies should explore the application’s long-term efficacy and replicability in larger community-based populations, with a focus on sustained engagement and adherence to rehabilitation programs.

PMID:40354624 | DOI:10.2196/63022

JCO Oncol Pract. 2025 May 12:OP2400978. doi: 10.1200/OP-24-00978. Online ahead of print.

ABSTRACT

PURPOSE: This study aimed to determine if high-deductible health plan (HDHP) enrollment contributes to financial burden and hinders access to care for patients with multiple myeloma (MM).

MATERIALS AND METHODS: Patients diagnosed with MM from 2010 to 2020 were identified in Merative MarketScan, an employer-based health insurance database. Primary outcomes were total health care and out-of-pocket (OOP) costs in the year after diagnosis. Secondary outcomes included time to treatment initiation and stem-cell transplant receipt. Multivariable analyses using linear, logistic, and Cox regression were performed, as appropriate. Covariates included age, sex, year diagnosed, comorbidities, data provider, and stem-cell transplant receipt.

RESULTS: The cohort included 4,029 patients; 17.6% were enrolled on HDHPs. HDHP enrollees were younger (mean age, 54.9 v 55.5 years; P = .036). Over the first year, mean total and OOP costs were $406,401 in US dollars (USD) and $9,220 USD for HDHP enrollees, respectively, versus $386,802 USD (P = .027) and $7,021 USD (P < .001) for the standard plan enrollees. There was no statistically significant difference in total cost (β = 11; P = .999) but mean OOP costs were $2,544 USD (β = 2,544; P < .001) higher for HDHP enrollees after adjusting for covariates. The additional OOP costs incurred in the first 2 months, presumably because of deductibles, and after the deductible reset. Contrary to our hypothesis, HDHPs enrollees had shorter time to treatment initiation (median, 20 v 22 days; hazard ratio, 1.18; P < .001) and were more likely to receive a stem-cell transplant (55.1% v 47.6%; odds ratio, 1.25; P = .010), after adjusting for covariates.

CONCLUSION: Compared with standard plan enrollees, OOP costs were higher for HDHP enrollees in the year after diagnosis, but HDHP enrollment was not associated with delays in treatment initiation or reduced access to stem-cell transplant.

PMID:40354593 | DOI:10.1200/OP-24-00978

Res Q Exerc Sport. 2025 May 12:1-13. doi: 10.1080/02701367.2025.2478870. Online ahead of print.

ABSTRACT

The objective of the present study was to ascertain whether the association between moderate-to-vigorous intensity physical activity (MVPA) levels and individual, interpersonal, organizational, and environmental factors among school children is influenced by their attitudes toward emerging sports participants (ESP). To this end, machine learning (ML) was employed to analyze the data. This cross-sectional study, involved 655 child-parent pairs in Changsha City to assess children’s MVPA. Data were collected via self-administered questionnaires, evaluating MVPA levels and attitudes from children and caregivers. Various statistical models, including random forest and LASSO regression, were utilized for analysis. The study revealed that boys engaged in more MVPA than girls. Most participants liked ESP, with significant teacher support noted. Random forest and LASSO regression models identified key factors influencing MVPA, with notable variability among non-achievers. The gradient boosting machine and K-nearest neighbors models demonstrated similar predictive performance. The final model, comprising 37 parameters, indicated significant relationships between variables, particularly highlighting the importance of school offerings ESP and living near sports field. This study concludes that offering ESP in schools, along with positive modeling and encouragement from caregivers and peers, effectively enhances children’s participation in MVPA. Living near sports field also positively impacts MVPA levels.

PMID:40354575 | DOI:10.1080/02701367.2025.2478870

J Occup Environ Hyg. 2025 May 12:1-11. doi: 10.1080/15459624.2025.2496492. Online ahead of print.

ABSTRACT

This study assessed the performance of the Institute of Occupational Medicine (IOM) and Gesamtstaubprobenahme (GSP) personal inhalable aerosol samplers in measuring aerosol and soluble protein (SP) concentrations across 12 food industry environments. A total of 193 sampling pairs (GSP and IOM) were analyzed for inhalable aerosols, and 185 sampling pairs for SP. Median aerosol concentrations ranged from 0.2 mg/m³ in snacks, nuts, and chips production to 5.6 mg/m³ in spreads production. The IOM sample had a median aerosol concentration of 1.8 mg/m³, while the GSP had a slightly lower median of 1.4 mg/m³, generally collecting 17% less inhalable aerosol than the IOM in most environments. The IOM also included wall deposits in its gravimetric determinations, contributing an additional 10-30% to the overall aerosol concentrations. For SP concentrations, the IOM measured higher aerosol concentrations in environments with a particle size distribution dominated by larger particles, while the GSP showed higher SP concentrations in environments dominated by smaller, respirable particles. The Tobit mixed-effect models showed that the IOM had statistically significantly higher aerosol concentrations compared to the GSP, but significantly lower SP concentrations than the GSP. However, these differences between the samplers were relatively small, suggesting that in occupational hygiene practices, both samplers can be used.

PMID:40354574 | DOI:10.1080/15459624.2025.2496492

Scand J Work Environ Health. 2025 May 12:4230. doi: 10.5271/sjweh.4230. Online ahead of print.

ABSTRACT

OBJECTIVES: This study aimed to (i) examine variance in the prevalence of workplace violence and fear of violence in the United Kingdom by industrial sector and (ii) determine the mental health effects thereof using longitudinal data.

METHODS: We used the United Kingdom Household Panel Study (UKHLS), a nationally representative survey with mental health indicators collected annually allowing us to determine common mental disorders (CMD) at baseline, one year prior and one year later. Using weighted logistic regression and lagged dependent variable regression, we examined prevalence of violence and fear of violence by sector and the effect of violence on CMD risk. We supplemented our analyses with the views of those with lived experience.

RESULTS: Workers employed in public administration and facilities had the highest risks of workplace violence, with predicted probabilities (PP) of 0.138 [95% confidence interval (CI) 0.116-0.160], and these were not statistically different from the second highest sector of health, residential care, and social work (PP 0.118, 95% CI 0.103-0.133). Workplace violence increased CMD risk [adjusted odds ratio (ORadj) 1.400, 95% CI 1.182-1.658] as did fear of violence at work (ORadj 2.103, 95% CI 1.779-2.487), adjusting for prior CMD. Moreover, the effect of violence and fear of violence on CMD remained when we investigated CMD one year later.

CONCLUSIONS: A high prevalence of workplace violence and fear of workplace violence was found in multiple different industrial sectors – >1 in 10 workers were exposed to violence in the last 12 months in 30% of sectors and >1 in 20 workers were exposed in 70% of sectors. Both violence and fear of violence were associated with enhanced CMD risk at baseline and one year later.

PMID:40354568 | DOI:10.5271/sjweh.4230

Age Ageing. 2025 May 3;54(5):afaf116. doi: 10.1093/ageing/afaf116.

ABSTRACT

INTRODUCTION: Time to surgery (TTS) increases mortality risk in old patients with proximal femur fractures (PFFs). Orthogeriatric care pathways reduce mortality and length of stay, but the interaction between TTS and geriatric intervention remains unclear.

OBJECTIVE: To identify organisational variables-including geriatric intervention-that are predictive of 90-day mortality and explore their interactions with TTS.

MATERIALS AND METHODS: This retrospective study included 7756 PFFs aged over 60 who underwent surgery between 2005 and 2017. Organisational factors influencing 90-day mortality (main outcome) were identified in an administrative database using log-rank tests. Variables such as a mobile geriatric team (MGT) intervening in the emergency department were screened. Selected variables were included in a Cox model alongside TTS and the AtoG score, a validated multidimensional prognostic tool (from 0 no comorbidity to ≥5). Statistical interactions between TTS and organisational variables were calculated.

RESULTS: MGT was one of the rare organisational variables with a protective effect: hazard ratio (HR) = 0.81, CI 95% [0.68-0.98], P = 0.03. MGT’s strongest effect was for TTS up to 1 day (HR = 0.70, CI95% [0.53-0.92], P = 0.01) and then decreased beyond 2 days (HR = 0.97, CI95% [0.73-1.3], P = 0.08). In patients with an AtoG score ≤ 2, MGT was the strongest parameter: HR = 0.76, CI95% [0.60-0.93], P = 0.03, while the HR for TTS was 1.01 CI 95% [0.99; 1.02], P = 0.15. In patients with an AtoG>2, there was a synergic interaction between MGT and reduced TTS (P = 0.05).

CONCLUSION: Geriatric intervention modulated the effect of TTS on 90-day mortality up to a TTS of 2 days. MGT had a positive impact on both vulnerable and earthier patients.

PMID:40354561 | DOI:10.1093/ageing/afaf116

Annu Rev Nutr. 2025 May 12. doi: 10.1146/annurev-nutr-111124-092627. Online ahead of print.

ABSTRACT

The US Department of Agriculture’s Gus Schumacher Nutrition Incentive Program (GusNIP) funds produce prescription (PPR) programs that allow healthcare to support patients in accessing fruits and vegetables. This hybrid systematic narrative review identified 16 studies of PPR programs associated with GusNIP funding in some way that examined health outcomes, including clinical measures and healthcare utilization. Program designs were heterogeneous, sample sizes were generally small, and methodological rigor was often low, with most studies using a prepost design and none using a randomized control group. Fewer than half of the studies examining clinical values showed an association between PPR participation and improved health outcomes (for example, three of eight studies measuring weight or body mass index showed a statistically significant reduction, as well as two of the six studies measuring glycosylated hemoglobin). Only three studies examined healthcare utilization, two of which showed improvements in hospitalization and/or emergency department utilization. Overall, evidence for the health impact of PPRs is nascent but growing. PPRs with capacity should engage in rigorous study designs and examine a variety of downstream health and utilization outcomes.

PMID:40354556 | DOI:10.1146/annurev-nutr-111124-092627