Tag: nevin manimala

Chem Biodivers. 2025 May 21:e00561. doi: 10.1002/cbdv.202500561. Online ahead of print.

ABSTRACT

Teucrium montanum is an evergreen shrub that is widespread in Europe. The aim of this study was to determine the composition of the essential oils of T. montanum and their relationship to ecology, morphology and genetics. The essential oils were analysed by gas chromatography-mass spectrometry and the data were evaluated by multivariate statistics and multiple regression. This species showed a remarkable variability of essential oils in the Balkan Peninsula. All registered compounds were used to define four chemotypes that showed no spatial regularity and did not correlate with most bioclimatic parameters. The classification of samples into chemotypes and different categorical variables proved to be completely independent. Moreover, the identified compounds showed no correlation with the bioclimatic parameters, including other categorical variables. To study such a complex phenomenon as the variation of essential oils of T. montanum, a different sampling approach must be adopted (e.g., ‘one individual, one sample’), but this could affect the viability of the population of this species.

PMID:40397960 | DOI:10.1002/cbdv.202500561

PLoS One. 2025 May 21;20(5):e0324497. doi: 10.1371/journal.pone.0324497. eCollection 2025.

ABSTRACT

This paper presents a novel longitudinal study examining interactions in healthcare expenditure (HCE). Utilizing fuzzy-set qualitative comparative analysis (fsQCA), the study constructs a consumption-provision-finance model to investigate factors influencing HCE. Data from the Organization for Economic Cooperation and Development (OECD) database for the years 2010-2022 are analyzed, covering 37 OECD countries (excluding Luxembourg due to insufficient data). By treating each country-year OECD observation as a case, causal recipes are identified and interpreted. The characteristics of the panel data set are examined by assessing the stability of causal patterns over multiple years and exploring the consistency of these patterns within individual countries across various years. The findings of this study offer significant insights for policy management and future research, particularly in relation to the diverse annual relationships observed between factors and HCE in different countries. Additionally, comparisons are drawn between panel fsQCA and cross-sectional fsQCA conducted for specific years.

PMID:40397958 | DOI:10.1371/journal.pone.0324497

PLoS One. 2025 May 21;20(5):e0323815. doi: 10.1371/journal.pone.0323815. eCollection 2025.

ABSTRACT

The COVID-19 pandemic highlighted the crucial role of vaccines in controlling the virus. Despite their effectiveness, however, vaccine hesitancy remained a challenge, particularly within certain population groups. This multi-disciplinary study investigates the diverse socio-demographic factors influencing COVID-19 vaccination decisions in the United States. Through a nationally representative survey of 5,240 people, the research explores the interplay of information sources, religious beliefs, political party, and demographic characteristics of the respondents. Our findings reveal associations of main sources of information with vaccination likelihood, with the Centers for Disease Control and Prevention demonstrating the highest association with full vaccination. Religious beliefs are significant determinants, with Evangelical Protestants exhibiting the lowest vaccination rates. We also highlight the intricate relationship between political leanings and vaccination behavior, emphasizing higher levels of vaccination among Democrats. Demographic variables, including age, education, gender, and race/ethnicity, also play pivotal roles, exposing disparities in vaccination access and decisions. In particular, older individuals and those with higher levels of education show a greater inclination to achieve full vaccination, while women and African Americans are less likely to attain complete vaccination. Lastly, while major ethnoracial groups seem to respond to different sources of information similarly, there are also nuanced differences, such as Asians being especially likely to be fully vaccinated if they depend on the CDC or other health sources while more disadvantaged groups seem less responsive to these sources. Overall, this research provides a comprehensive analysis of the nuanced factors shaping vaccination behavior. It contributes valuable knowledge to public health strategies, emphasizing the need for targeted communication campaigns tailored to diverse communities.

PMID:40397952 | DOI:10.1371/journal.pone.0323815

JMIR Res Protoc. 2025 May 21;14:e63627. doi: 10.2196/63627.

ABSTRACT

BACKGROUND: Hearing loss is a common late effect in childhood cancer survivors, caused by ototoxic cancer treatments, such as platinum chemotherapy, cranial radiation with doses of ≥30 Gray, and surgery involving the auditory system. Early recognition of hearing loss as part of follow-up care allows for therapeutic support to mitigate consequences. However, hearing tests are usually only repeated in childhood cancer survivors with abnormal hearing during or right after treatment ends, leaving hearing loss undetected in childhood cancer survivors with late onset or when missed during cancer treatment. Further, general follow-up care attendance may be low after childhood cancer survivors transition to adult care, contributing to missing hearing screening posttherapy. Low attendance may be attributed to childhood cancer survivors finding follow-up care burdensome and time-consuming, lacking awareness of their risk for certain late effects, or the absence of suitable interdisciplinary follow-up clinics. A low-threshold, easily accessible screening program requiring minimal participant effort may address these barriers and improve access to hearing loss screening for childhood cancer survivors.

OBJECTIVE: The HEAR study aims to develop, conduct, and evaluate the feasibility of a low-threshold, community-based screening program for hearing loss in childhood cancer survivors, using the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework, a tool to plan and evaluate health interventions. Within the screening program, participating childhood cancer survivors completed a standardized hearing assessment at a local Swiss hearing aid provider’s shop. This approach provides low-threshold access to detect hearing loss as it is easily and conveniently accessible for everyone.

METHODS: Eligible childhood cancer survivors were identified through the Childhood Cancer Registry Switzerland and included those diagnosed with cancer between 1976 and 2019 before 21 years and who were ≥2 years post diagnosis. We invited eligible childhood cancer survivors by post. Participants scheduled a hearing test appointment at a hearing aid shop. They completed a baseline questionnaire before the hearing test, and 2 follow-up questionnaires afterward to assess program feasibility and participant experiences. Semistructured interviews with participants, hearing aid shop staff, and group discussions with health care professionals will provide qualitative insights. The RE-AIM framework will guide the program evaluation using the quantitative and qualitative data collected.

RESULTS: As of February 2025, all participants have been recruited, and all steps of the study up to the group discussions and the RE-AIM evaluation have been completed.

CONCLUSIONS: The HEAR study introduces a novel, simple, and low-threshold approach to screening for hearing loss after cancer treatment through hearing aid shops located in the community and close to participants’ homes. This approach has the potential to supplement existing follow-up care programs by reducing the burden of hearing screening for adult childhood cancer survivors and reaching those who might otherwise be lost to follow-up.

TRIAL REGISTRATION: ClinicalTrials.gov NCT06036407; https://clinicaltrials.gov/study/NCT06036407.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/63627.

PMID:40397950 | DOI:10.2196/63627

JMIR Aging. 2025 May 21;8:e70302. doi: 10.2196/70302.

ABSTRACT

BACKGROUND: Cyberchondria is the compulsive searching for health information online that continues despite harmful effects. It leads to increased health anxiety and lower health-related quality of life (HRQOL). Older adults face higher risks of cyberchondria due to their limited digital literacy skills and more frequent health concerns. However, researchers have not thoroughly studied how cyberchondria affects this age group.

OBJECTIVE: This study aimed to explore cyberchondria in the older population and investigate its relationship with cognitive fusion (ie, the tendency to become entangled with thoughts and perceive them as literal truths that dictate behavior), HRQOL, and mental well-being.

METHODS: A web-based, cross-sectional survey was conducted in May 2024 with a sample of 638 participants from China aged ≥60 years recruited through the online panel of a survey company. The participants completed questionnaires assessing cyberchondria (using the Cyberchondria Severity Scale-12 [CSS-12]), cognitive fusion, HRQOL, and mental well-being. Structural equation modeling (SEM) was used to assess the hypothesized mediation model, and standardized estimates and their 95% CIs were calculated for all structural paths.

RESULTS: Participants had a mean CSS-12 score of 40 (SD 8.5), suggesting a fairly high level of cyberchondria in this sample. Participants with a higher socioeconomic status tended to report lower levels of cyberchondria. The SEM showed that cyberchondria was positively associated with cognitive fusion (β=0.505, P<.001 for both models) and negatively associated with HRQOL (β=-0.221, P<.001) and mental well-being (β=-0.212, P<.001). The mediation model showed a good fit and demonstrated that cognitive fusion fully mediated the total effect of cyberchondria on HRQOL and mental well-being.

CONCLUSIONS: Cyberchondria may be more prominent in older Chinese adults, especially those residing in rural areas and with a lower socioeconomic status. Additionally, cyberchondria can enhance cognitive fusion, contributing to poor HRQOL and mental well-being. Interventions focused on “defusing” cyberchondria-relevant thoughts may help reduce maladaptive behaviors associated with cyberchondria and improve the overall well-being of older populations.

PMID:40397949 | DOI:10.2196/70302

JMIR Serious Games. 2025 May 21;13:e65878. doi: 10.2196/65878.

ABSTRACT

BACKGROUND: Exergame-based training enhances physical and cognitive performance in older adults, including those with mild neurocognitive disorder (mNCD). In-game metrics generated from user interactions with exergames enable individualized adjustments. However, there is a need to systematically investigate how well such game metrics capture true cognitive and motor-cognitive performance to provide a more robust basis for personalized training.

OBJECTIVE: The primary objective was to identify valid game metrics as indicators for in-game domain-specific cognitive performance during exergaming in individuals with mNCD. We also aimed to explore game metric performance changes over time during exergame-based training.

METHODS: Data were analyzed from individuals with mNCD who completed a 12-week home-based, exergame-based intervention following the Brain-IT training concept. A cross-sectional analysis was conducted by correlating game metrics with standardized neurocognitive reference assessments. To confirm the alternative hypothesis, we predetermined the following criteria: (1) statistically significant correlation (P≤.05; uncorrected; 1-sided) with (2) a correlation coefficient (Pearson r or Spearman ρ) of ≥0.4. Visual and curve-fitting longitudinal analyses were conducted to explore game performance changes over time.

RESULTS: Data were available from 31 participants (mean age 76.4, SD 7.5 y; n=9, 29% female). In total, 33% (6/18) of the game metrics were identified as valid indicators for in-game cognitive performance during exergaming. In the neurocognitive domain of learning and memory, these metrics included the mean reaction time (ρ=-0.747), the number of collected items (ρ=0.691), and the precision score (r=-0.607) for the game Shopping Tour (P<.001 in all cases), as well as the point rate (P=.008; r=0.471) for the game Simon. In addition, point rate was a valid indicator for executive function (P=.006; r=0.455) and visuospatial skills (P=.02; r=0.474) for the games Targets and Gears, respectively. The exploratory longitudinal analysis revealed high interindividual variability, with a general trend of the expected typical curvilinear curves of rapid initial improvements followed by a plateau in performance.

CONCLUSIONS: This study demonstrated that metrics reflecting the precision of responses generally performed better than metrics reflecting the speed of responses. These observations highlight the importance of selecting valid game metrics for implementation in exergame designs. Further research is needed to explore the potential of game metrics and identify factors contributing to individual variability in in-game performance and performance progression, as well as identifying and adopting strategies that facilitate individual learning success and thus promote effectiveness in improving health outcomes.

PMID:40397948 | DOI:10.2196/65878

J Med Internet Res. 2025 May 21;27:e67462. doi: 10.2196/67462.

ABSTRACT

BACKGROUND: Telemedicine, which incorporates artificial intelligence such as chatbots, offers significant potential for enhancing health care delivery. However, the efficacy of artificial intelligence chatbots compared to human physicians in clinical settings remains underexplored, particularly in complex scenarios involving patients with cancer and asynchronous text-based interactions.

OBJECTIVE: This study aimed to evaluate the performance of the GPT-4 (OpenAI) chatbot in responding to asynchronous text-based medical messages from patients with cancer by comparing its responses with those of physicians across two clinical scenarios: patient education and medical decision-making.

METHODS: We collected 4257 deidentified asynchronous text-based medical consultation records from 17 oncologists across China between January 1, 2020, and March 31, 2024. Each record included patient questions, demographic data, and disease-related details. The records were categorized into two scenarios: patient education (eg, symptom explanations and test interpretations) and medical decision-making (eg, treatment planning). The GPT-4 chatbot was used to simulate physician responses to these records, with each session conducted in a new conversation to avoid cross-session interference. The chatbot responses, along with the original physician responses, were evaluated by a medical review panel (3 oncologists) and a patient panel (20 patients with cancer). The medical panel assessed completeness, accuracy, and safety using a 3-level scale, whereas the patient panel rated completeness, trustworthiness, and empathy on a 5-point ordinal scale. Statistical analyses included chi-square tests for categorical variables and Wilcoxon signed-rank tests for ordinal ratings.

RESULTS: In the patient education scenario (n=2364), the chatbot scored higher than physicians in completeness (n=2301, 97.34% vs n=2213, 93.61% for fully complete responses; P=.002), with no significant differences in accuracy or safety (P>.05). In the medical decision-making scenario (n=1893), the chatbot exhibited lower accuracy (n=1834, 96.88% vs n=1855, 97.99% for fully accurate responses; P<.001) and trustworthiness (n=860, 50.71% vs n=1766, 93.29% rated as “Moderately trustworthy” or higher; P<.001) compared with physicians. Regarding empathy, the medical review panel rated the chatbot as demonstrating higher empathy scores across both scenarios, whereas the patient review panel reached the opposite conclusion, consistently favoring physicians in empathetic communication. Errors in chatbot responses were primarily due to misinterpretations of medical terminology or the lack of updated guidelines, with 3.12% (59/1893) of its responses potentially leading to adverse outcomes, compared with 2.01% (38/1893) for physicians.

CONCLUSIONS: The GPT-4 chatbot performs comparably to physicians in patient education by providing comprehensive and empathetic responses. However, its reliability in medical decision-making remains limited, particularly in complex scenarios requiring nuanced clinical judgment. These findings underscore the chatbot’s potential as a supplementary tool in telemedicine while highlighting the need for physician oversight to ensure patient safety and accuracy.

PMID:40397947 | DOI:10.2196/67462

PLoS Comput Biol. 2025 May 21;21(5):e1012993. doi: 10.1371/journal.pcbi.1012993. eCollection 2025 May.

ABSTRACT

Vertex models provide a robust theoretical framework for studying epithelial tissues as a network of cell boundaries. They have been pivotal in exploring properties such as cell packing geometry and rigidity transitions. Recently, extended vertex models have become instrumental in bridging the subcellular scales to the tissue scale. Here, we review extensions of the model aiming to capture experimentally observed subcellular features of epithelial tissues including heterogeneity in myosin activity across the tissue, non-uniform contractility structures, and mechanosensitive feedback loops. We discuss how these extensions change and challenge current perspectives on observables of macroscopic tissue properties. First, we find that extensions to the vertex model can change model properties significantly, impacting the critical threshold and in some cases even the existence of a rigidity transition. Second, we find that packing disorder can be explained by models employing different subcellular mechanisms, indicating a source of stochasticity and gradual local size changes as common mesoscopic motifs in the mechanics of tissue organization. We address complementary models and statistical inference, putting vertex models in a broader methodological context and we give a brief overview of software packages utilized in increasingly complex vertex model studies. Our review emphasizes the need for more comparative, systematic studies that identify specific classes of vertex models which share a set of well-defined properties, as well as a more in-depth discussion of modeling choices and their biological motivations.

PMID:40397938 | DOI:10.1371/journal.pcbi.1012993

JMIR Med Inform. 2025 May 21;13:e63906. doi: 10.2196/63906.

ABSTRACT

BACKGROUND: Despite wide acceptance in medical research, implementation of the FAIR (findability, accessibility, interoperability, and reusability) principles in certain health domains and interoperability across data sources remain a challenge. While clinical trial registries collect metadata about clinical studies, numerous epidemiological and public health studies remain unregistered or lack detailed information about relevant study documents. Making valuable data from these studies available to the research community could improve our understanding of various diseases and their risk factors. The National Research Data Infrastructure for Personal Health Data (NFDI4Health) seeks to optimize data sharing among the clinical, epidemiological, and public health research communities while preserving privacy and ethical regulations.

OBJECTIVE: We aimed to develop a tailored metadata schema (MDS) to support the standardized publication of health studies’ metadata in NFDI4Health services and beyond. This study describes the development, structure, and implementation of this MDS designed to improve the FAIRness of metadata from clinical, epidemiological, and public health research while maintaining compatibility with metadata models of other resources to ease interoperability.

METHODS: Based on the models of DataCite, ClinicalTrials.gov, and other data models and international standards, the first MDS version was developed by the NFDI4Health Task Force COVID-19. It was later extended in a modular fashion, combining generic and NFDI4Health use case-specific metadata items relevant to domains of nutritional epidemiology, chronic diseases, and record linkage. Mappings to schemas of clinical trial registries and international and local initiatives were performed to enable interfacing with external resources. The MDS is represented in Microsoft Excel spreadsheets. A transformation into an improved and interactive machine-readable format was completed using the ART-DECOR (Advanced Requirement Tooling-Data Elements, Codes, OIDs, and Rules) tool to facilitate editing, maintenance, and versioning.

RESULTS: The MDS is implemented in NFDI4Health services (eg, the German Central Health Study Hub and the Local Data Hub) to structure and exchange study-related metadata. Its current version (3.3) comprises 220 metadata items in 5 modules. The core and design modules cover generic metadata, including bibliographic information, study design details, and data access information. Domain-specific metadata are included in use case-specific modules, currently comprising nutritional epidemiology, chronic diseases, and record linkage. All modules incorporate mandatory, optional, and conditional items. Mappings to the schemas of clinical trial registries and other resources enable integrating their study metadata in the NFDI4Health services. The current MDS version is available in both Excel and ART-DECOR formats.

CONCLUSIONS: With its implementation in the German Central Health Study Hub and the Local Data Hub, the MDS improves the FAIRness of data from clinical, epidemiological, and public health research. Due to its generic nature and interoperability through mappings to other schemas, it is transferable to services from adjacent domains, making it useful for a broader user community.

PMID:40397930 | DOI:10.2196/63906

J Med Internet Res. 2025 May 21;27:e60284. doi: 10.2196/60284.

ABSTRACT

BACKGROUND: The recent emergence of wearable devices has made feasible the passive gathering of intensive, longitudinal data from large groups of individuals. This form of data is effective at capturing physiological changes between participants (interindividual variability) and changes within participants over time (intraindividual variability). The emergence of longitudinal datasets provides an opportunity to quantify the contribution of such longitudinal data to the control of these sources of variability for applications such as responder analysis, where traditional, sparser sampling methods may hinder the categorization of individuals into these phenotypes.

OBJECTIVE: This study aimed to quantify the gains made in statistical power and effect size among statistical comparisons when controlling for interindividual variability and intraindividual variability compared with controlling for neither.

METHODS: Here, we test the gains in statistical power from controlling for interindividual and intraindividual variability of resting heart rate, collected in 2020 for over 40,000 individuals as part of the TemPredict study on COVID-19 detection. We compared heart rate on weekends with that on weekdays because weekends predictably change the behavior of most individuals, though not all, and in different ways. Weekends also repeat consistently, making their effects on heart rate feasible to assess with confidence over large populations. We therefore used weekends as a model system to test the impact of different statistical controls on detecting a recurring event with a clear ground truth. We randomly and iteratively sampled heart rate from weekday and weekend nights, controlling for interindividual variability, intraindividual variability, both, or neither.

RESULTS: Between-participant variability appeared to be a greater source of structured variability than within-participant fluctuations. Accounting for interindividual variability through within-individual sampling required 40× fewer pairs of samples to achieve statistical significance with 4× to 5× greater effect size at significance. Within-individual sampling revealed differential effects of weekends on heart rate, which were obscured by aggregated sampling methods.

CONCLUSIONS: This work highlights the leverage provided by longitudinal, within-individual sampling to increase statistical power among populations with heterogeneous effects.

PMID:40397926 | DOI:10.2196/60284