Nevin Manimala

J Ethn Subst Abuse. 2025 Jun 17:1-18. doi: 10.1080/15332640.2025.2517776. Online ahead of print.

ABSTRACT

College students indicate high use of alcohol and marijuana; cultural influences may affect substance use. This study assessed the associations between alcohol and marijuana past 30-day use, and microaggressions, acculturation, and familism among Latinx college students. Participants (n = 484) completed measures, and structural equation modeling was used to yield results. Findings suggested that microaggressions were a risk factor for alcohol use, (B = -1.29, p = .007) while acculturation was a risk factor for marijuana use (B = 1.06, p = .011). No other statistically significant associations with alcohol or marijuana past 30-day use were observed. Culturally based prevention and intervention efforts appear warranted.

PMID:40526820 | DOI:10.1080/15332640.2025.2517776

Nurs Open. 2025 Jun;12(6):e70243. doi: 10.1002/nop2.70243.

ABSTRACT

Universal accessibility is one of the most active lines of action among the steps to mitigate and compensate the restriction in participation and the limitation of activity in people with disabilities. Occupational therapists often work in a person’s natural environment to assess and intervene in occupational performance. In addition to being a tool for evaluating the accessibility of individuals who visit community health professionals, especially nursing staff, this resource can significantly improve patient care and outreach efforts.

OBJECTIVE: The main aim of this study was to create and validate an instrument to measure the limitations in the activity of each person related to the vertical accessibility of their home.

DESIGN: The methodology of this work is a psychometric design. This is a process of construct validation of a vertical accessibility scale through confirmatory factor analysis.

METHODS: The scale construction is carried out following a content validation process, involving the participation of five expert occupational therapists, and the analysis of their contributions using the Attribute Agreement Analysis. In this process, Fleiss Kappa statistical analysis is used, and Kendal’s W is included due to the utilisation of ordinal variables. For the construct validation of the tool, the most suitable process is followed, an Exploratory Factor Analysis, and subsequent Confirmatory Factor Analysis using Global Absolute Adjustment indices for all the subscales of the test. The analysis of the indicators was performed using the weighted least squares (DWLS) estimation method. An initial test of 63 items distributed into four subscales was configured based on the different determined accessibility spaces: (a) exterior areas and access to the building/living space; (b) horizontal mobility inside the building and common areas; (c) vertical mobility of the building/living spaces and (d) access to and the entrance door as well as the interior of the living spaces.

RESULTS: Once the analysis has been carried out with the absolute fit indices obtaining excellent values, the validation process is concluded and the final scale with 48 items is finalised. This validation process allows us to affirm that it is a useful and viable tool to evaluate accessibility. No public or patient contribution.

PMID:40526819 | DOI:10.1002/nop2.70243

Br J Surg. 2025 May 31;112(6):znaf075. doi: 10.1093/bjs/znaf075.

ABSTRACT

BACKGROUND: Removal of Kirschner wires (K-wires) after fracture treatment in the upper limb is unpleasant for children. The aim of this study was to evaluate whether virtual reality (VR) distraction could improve pain and the overall experience for children.

METHODS: An RCT was performed in a single outpatient fracture clinic, where children (aged 6-15 years) were randomized 1 : 1, in three age strata, to additional VR or standard of care. Pain perception was assessed using the Wong-Baker Faces Pain Rating Scale by neutral observers and later by the patients and their guardians. Further measures included the Face/Legs/Activity/Cry/Consolability (FLACC) Pain Scale, the modified Yale Pain Anxiety Scale (mYPAS), and questionnaires, as well as objective data, such as heart rate variability and blood pressure.

RESULTS: A total of 146 patients were recruited into the trial. The VR group showed significantly less pain on the Wong-Baker Faces Pain Rating Scale (OR 0.23 (95% c.i. 0.12 to 0.43)) compared with the control group. Observers rated the pain >2 for 43% of patients in the VR group and 74% of patients in the control group. Observer scales (the FLACC Pain Scale and the mYPAS) during K-wire removal also indicated less pain (OR 0.36 (95% c.i. 0.19 to 0.24) and 0.29 (95% c.i. 0.16 to 0.52) respectively). The difference in pain rated >2 between the VR and control group was smaller directly after (59% versus 69% respectively) and 2 weeks after (58% versus 70% respectively) K-wire removal. Children in the VR group were less aware of the painful stimulus directly after and 2 weeks after wire extraction.

CONCLUSION: VR distraction effectively reduces pain during K-wire removal in children. VR positively impacts the procedural memory of children.

REGISTRATION NUMBER: DRKS00020229 (Deutsches Register Klinischer Studien (DRKS; that is the German Clinical Trials Register); date of registration 10 December 2019).

PMID:40526816 | DOI:10.1093/bjs/znaf075

Sex Health. 2025 Jun;22:SH24230. doi: 10.1071/SH24230.

ABSTRACT

Background Despite partner notification (PN) being an essential component of sexually transmitted infection (STI) control programs, little is known about how contacts of STIs are notified, and the time taken to present for testing. We aimed to evaluate both aspects in people presenting to Sydney Sexual Health Centre who reported being a sexual contact of someone diagnosed with an STI. Methods We conducted a retrospective observational study of data collected between 1 April 2020 and 31 March 2021 at Sydney Sexual Health Centre. A pop-up field in the electronic medical record collected data about people’s experience of being notified of their sexual contact with an STI. We ran univariable and multivariable analysis of time to presentation and PN method against clinical and demographic information. Results There were 2182 presentations because of STI contact notification. Median time to presentation was 3days (IQR 1-7days), which did not differ by spoken or electronic PN. In the multivariable model, people who received spoken PN were less likely to present in P =0.007). This indicates electronic PN may prompt faster testing for STIs. Higher partner number was associated with receiving electronic PN. Conclusions Our study suggests that electronic PN may prompt faster testing for STIs. It provides valuable insights into the characteristics of STI contacts, who are rarely the focus of PN research. Understanding what motivates notified contacts to seek care is integral in modernising PN practices, as rates of STIs climb.

PMID:40526810 | DOI:10.1071/SH24230

PLoS One. 2025 Jun 17;20(6):e0321204. doi: 10.1371/journal.pone.0321204. eCollection 2025.

ABSTRACT

Many investors and financial managers view portfolio optimisation as a critical step in the management and selection processes. This is due to the fact that a portfolio fundamentally comprises a collection of uncertain securities, such as equities. For this reason, having a solid understanding of the elements responsible for these uncertainties is absolutely necessary. Investors will always look for a portfolio that can handle the required amount of risk while still producing the desired level of expected returns. This article uses feature-based models to investigate the primary elements that contribute to the optimal composition of a specific portfolio. These models make use of physical analyses, such as the Fourier transform, wavelet transforms and the Fourier-Mellin transform. Motivated by their use in medical analysis and detection, the purpose of this research was to analyse the efficacy of these methods in establishing the primary factors that go into optimising a particular portfolio. These geometric features are input into artificial neural networks, including convolutional and recurrent networks. These are then compared with other algorithms, such as vector autoregression, in portfolio optimisation tests. By testing these models on real-world data obtained from the US stock market, we were able to obtain preliminary findings on their utility.

PMID:40526747 | DOI:10.1371/journal.pone.0321204

PLoS One. 2025 Jun 17;20(6):e0321523. doi: 10.1371/journal.pone.0321523. eCollection 2025.

ABSTRACT

Globally, there is increasing attention on mental health promotion for young people because of its great public health and social significance. The scarcity of suitable mental health measures for young people underscores the urgent need for tailored interventions to address their unique mental health challenges. This study explores the reliability and validity of the self-rated mental health measurement scale (SRMHS) for assessing Chinese youth mental health in an urban context in China, addressing a critical research gap in culturally and contextually appropriate mental health measurement instruments. The study responds to the global demand for valid and reliable health data to support mental well-being initiatives. Utilizing a sample of 3,279 participants aged 14-35 years, the study employed rigorous statistical analyses, including Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), and tests for convergent, discriminant, and concurrent validity, to evaluate the scale’s psychometric properties. Results confirm a three-dimensional structure of the mental health scale, encompassing positive emotion, psychosocial symptoms and negative emotion, and cognitive function, demonstrating good internal consistency, reliability, and validity. Subgroup consistency categorized across gender, age, and social identity was examined, and the significant correlations between mental health scores with relevant psychological outcomes showed good concurrent validity, indicating the effectiveness of SRMHS in capturing a broad spectrum of psychological states relevant to youth development. Findings highlight the importance of a multidimensional approach to mental health assessment, reflecting global advocacy for recognizing mental well-being as not merely the absence of illness, but also the presence of positive psychological states. This study significantly contributes to the field by providing a scientifically robust and culturally sensitive tool for assessing youth mental health in China, and promotes a more inclusive and holistic approach to mental health research and practice globally. The results of this study could benefit policy-making, targeted interventions, and the overall improvement of youth mental well-being.

PMID:40526745 | DOI:10.1371/journal.pone.0321523

PLoS One. 2025 Jun 17;20(6):e0326079. doi: 10.1371/journal.pone.0326079. eCollection 2025.

ABSTRACT

Arrhythmia is a prevalent cardiac disorder that can lead to severe complications such as stroke and cardiac arrest. While deep learning has advanced automated ECG analysis, challenges remain in accurately classifying arrhythmias due to signal variability, data imbalance, and feature representation limitations. In this work, we propose a novel arrhythmia classification algorithm based on a multi-input convolutional neural network (CNN) enhanced with a Squeeze-and-Excitation (SE) attention mechanism. Distinct from previous methods that rely on single-resolution features or unimodal inputs, our model integrates multi-scale time-frequency representations derived from Short-Time Fourier Transform (STFT) applied to ECG signals segmented into two temporal resolutions. The dual-branch CNN architecture enables complementary feature learning from both short and long segments, while SE blocks enhance inter-channel dependencies to prioritize critical features. The fusion strategy combines feature maps via bicubic interpolation and element-wise summation to maintain spatial integrity. Evaluated on MIT-BIH and SPH arrhythmia databases, the proposed model achieves high accuracy (99.13% and 95.84%, respectively) and Macro-F1 scores (94.46% and 95.91%), outperforming several state-of-the-art approaches. These results highlight the model’s potential for robust and interpretable arrhythmia classification in clinical practice.

PMID:40526742 | DOI:10.1371/journal.pone.0326079

PLoS One. 2025 Jun 17;20(6):e0310163. doi: 10.1371/journal.pone.0310163. eCollection 2025.

ABSTRACT

BACKGROUND: Dengue is an acute febrile illness that is a significant public health problem. Peru is an endemic region for vector-borne diseases such as dengue, zika, and chikungunya, which initially manifest with febrile illness and can complicate differential diagnosis. Therefore, the present study aimed to determine the prevalence of positive results for dengue or dengue antibodies in Peruvian patients with febrile illness using diagnostic tools such as RT-PCR and ELISA NS1, IgM, and IgG.

METHODS: A literature search was conducted in eight databases or search tools (PubMed, Scopus, Embase, Web of Science, ScienceDirect, Google Scholar, Virtual Health Library, and Scielo) until June 9, 2024. Medical Subject Headings (MeSH) terms such as “dengue” and “Peru” were used, together with the free term “febrile illness”, combined using the Boolean operators AND and OR. We included observational studies with a control group of patients with fever but no dengue infection and a non-control group of febrile patients who tested positive for dengue. Pooled estimates and 95% confidence intervals (CI) were calculated using random-effects models. Study quality and risk of bias were assessed using the Joanna Briggs Institute Statistical Meta-Analysis Assessment and Review Instrument. Heterogeneity was assessed using the I2 statistic, and statistical analysis was performed with R version 4.2.3.

RESULTS: We included 15 observational studies that met the inclusion criteria developed in 10 regions of Peru and published between 2002 and 2022, with a total of 12,355 patients with febrile illness. The pooled prevalence of positive results for dengue or dengue antibodies in these patients was 21% (95% CI: 9%-36%; 2022 participants; 5 studies; I2 = 98%) for IgG ELISA, 16% (95% CI: 11%-21%; 10891 participants; 10 studies; I2 = 97%) for IgM ELISA, 19% (95% CI: 9%-31%; 2086 participants; 5 studies; I2 = 98%) for NS1 ELISA, and 20% (95% CI: 13%-28%; 3107 participants; 9 studies; I2 = 96%) for RNA PCR.

CONCLUSION: Our results suggest a high prevalence of positive results for dengue or dengue antibodies among febrile patients in Peru, which varies depending on the diagnostic method used. Despite this variability, the use of accurate diagnostic methods is essential for the early detection and prevention of serious complications. The findings underline the need to strengthen dengue control strategies, improve diagnostic capacity in health centers, and optimize epidemiological surveillance in high-incidence regions. It is recommended that public health policies focus on these key areas for better management of the disease.

PMID:40526741 | DOI:10.1371/journal.pone.0310163

PLoS One. 2025 Jun 17;20(6):e0326315. doi: 10.1371/journal.pone.0326315. eCollection 2025.

ABSTRACT

Type 2 diabetes (T2D) is considered a significant global health concern. Hemoglobin A1c level (HbA1c) is recognized as the most reliable indicator for its diagnosis. Genetic, family, environmental, and health behaviors are the factors associated with the disease. T2D is linked to substantial economic costs and human suffering, making it a primary concern for health planners, physicians, and those living with the disease. Saudi Arabia currently ranks seventh worldwide in terms of prevalence rate. Despite this high rate, the country lacks focused research on T2D. This study aims to develop hybrid prediction models that integrate the strengths of multiple algorithms to enhance HbA1c prediction accuracy while minimising the number of significant Key Performance Indicators (KPIs). The proposed model can help healthcare practitioners diagnose T2D at an early stage. Analyses were conducted in a case-control study in Saudi Arabia involving cases (patients with HbA1c levels ≥ 6.5) and controls with normal HbA1c levels (< 6.5). Medical records from 3,000 King Abdulaziz University Hospital patients containing demographic, lifestyle, and lipid profile data were used to develop the models. For the first time, we utilized recommended machine learning algorithms to develop hybrid prediction models to reduce the number of significant KPIs while enhancing HbA1c prediction accuracy. The hybrid model combining Random Forest (RF) and Logistic Regression (LR) with only 4 out of 10 KPIs outperformed other models with an accuracy of 0.93, precision of 0.95, recall of 0.90, F-score of 0.92, an AUC of 0.88, and Gini index of 0.76. The significant variables identified by the model through backward elimination are age, body mass index (BMI), triglycerides (TG), and high-density lipoprotein (HDL). The proposed model helps healthcare providers identify patients at risk of T2D by monitoring fewer key predictors of HbA1c levels, enhancing early intervention strategies for managing diabetes in Saudi Arabia.

PMID:40526740 | DOI:10.1371/journal.pone.0326315

J Clin Exp Neuropsychol. 2025 Jun 17:1-18. doi: 10.1080/13803395.2025.2521019. Online ahead of print.

ABSTRACT

OBJECTIVE: Emotional priming is modulated by word concreteness, yet the literature is inconsistent. This study investigates the effects of affect, lexical features, depressive symptoms, and rumination on emotional priming for abstract and concrete words.

METHODS: Eighty-one healthy participants (48 female, age = 24.12 ± 8.56 years) completed a valence categorization task in which they were asked to decide whether a target word, presented for 500 ms following a 65 ms prime, was pleasant, neutral, or unpleasant. Priming effect (PE) was defined as the RT difference between incongruent and congruent conditions for pleasant and unpleasant primes. Linear mixed-effects models were used to assess priming effects and error rates, with fixed effects for prime valence, concreteness, subscales of Positive and Negative Affect Scale, Beck Depression Inventory score, subscales of Rumination Response Scale, semantic relatedness and Levenshtein distance (LD). Model selection was performed using the buildmer algorithm. Post-hoc analyses of interactions and continuous predictor trends across categorical levels were performed using emmeans and emtrends. All statistical analyses were conducted by R 4.4.3.

RESULTS: PEs were stronger for concrete than abstract words, irrespective of prime valence. Positive affect predicted higher error rates for unpleasant targets and enhanced PEs for unpleasant primes, particularly in abstract words. Depressive symptoms were associated with fewer errors for unpleasant targets but did not predict PE. Brooding was associated with larger PEs for abstract words, independent of valence. Lastly, greater semantic relatedness amplified PEs for abstract items, whereas smaller LD both strengthened PEs and increased errors in valence‑incongruent trials.

CONCLUSION: This study highlights the role of emotional and clinical traits in word processing, showing that abstract word priming is driven by the interaction of affect and stimulus value. Future studies examining biases in abstract emotional word processing may guide the development of methods to identify individuals at risk for depression.

PMID:40525403 | DOI:10.1080/13803395.2025.2521019