Tag: nevin manimala

J Med Internet Res. 2025 Mar 10;27:e66321. doi: 10.2196/66321.

ABSTRACT

BACKGROUND: Young people are disproportionately impacted by self-harm and suicide, and concerns exist regarding the role of social media and exposure to unsafe content. Governments and social media companies have taken various approaches to address online safety for young people when it comes to self-harm and suicide; however, little is known about whether key stakeholders believe current approaches are fit-for-purpose.

OBJECTIVE: From the perspective of young people, policy makers and professionals who work within the social media industry, this study aimed to explore (1) the perceived challenges and views regarding young people communicating on social media about self-harm and suicide, and (2) what more social media companies and governments could be doing to address these issues and keep young people safe online.

METHODS: This qualitative study involved 6 focus groups with Australian young people aged 12-25 years (n=7), Australian policy makers (n=14), and professionals from the global social media industry (n=7). Framework analysis was used to summarize and chart the data for each stakeholder group.

RESULTS: In total, 3 primary themes and six subthemes are presented: (1) challenges and concerns, including the reasons for, and challenges related to, online communication about self-harm and suicide as well as reasoning with a deterministic narrative of harm; (2) roles and responsibilities regarding online safety and suicide prevention, including who is responsible and where responsibility starts and stops, as well as the need for better collaborations; and (3) future approaches and potential solutions, acknowledging the limitations of current safety tools and policies, and calling for innovation and new ideas.

CONCLUSIONS: Our findings highlight tensions surrounding roles and responsibilities in ensuring youth online safety and offer perspectives on how social media companies can support young people discussing self-harm and suicide online. They also support the importance of cross-industry collaborations and consideration of social media in future suicide prevention solutions intended to support young people.

PMID:40063940 | DOI:10.2196/66321

J Med Internet Res. 2025 Mar 10;27:e50313. doi: 10.2196/50313.

ABSTRACT

BACKGROUND: eHealth literacy has increasingly emerged as a critical determinant of health, highlighting the importance of identifying its influencing factors; however, these factors remain unclear. Numerous studies have explored this concept across various populations, presenting an opportunity for a systematic review and synthesis of the existing evidence to better understand eHealth literacy and its key determinants.

OBJECTIVE: This study aimed to provide a systematic review of factors influencing eHealth literacy and to examine their impact across different populations.

METHODS: We conducted a comprehensive search of papers from PubMed, CNKI, Embase, Web of Science, Cochrane Library, CINAHL, and MEDLINE databases from inception to April 11, 2023. We included all those studies that reported the eHealth literacy status measured with the eHealth Literacy Scale (eHEALS). Methodological validity was assessed with the standardized Joanna Briggs Institute (JBI) critical appraisal tool prepared for cross-sectional studies. Meta-analytic techniques were used to calculate the pooled standardized β coefficient with 95% CIs, while heterogeneity was assessed using I2, the Q test, and τ2. Meta-regressions were used to explore the effect of potential moderators, including participants’ characteristics, internet use measured by time or frequency, and country development status. Predictors of eHealth literacy were integrated according to the Literacy and Health Conceptual Framework and the Technology Acceptance Model (TAM).

RESULTS: In total, 17 studies met the inclusion criteria for the meta-analysis. Key factors influencing higher eHealth literacy were identified and classified into 3 themes: (1) actions (internet usage: β=0.14, 95% CI 0.102-0.182, I2=80.4%), (2) determinants (age: β=-0.042, 95% CI -0.071 to -0.020, I2=80.3%; ethnicity: β=-2.613, 95% CI -4.114 to -1.112, I2=80.2%; income: β=0.206, 95% CI 0.059-0.354, I2=64.6%; employment status: β=-1.629, 95% CI -2.323 to -0.953, I2=99.7%; education: β=0.154, 95% CI 0.101-0.208, I2=58.2%; perceived usefulness: β=0.832, 95% CI 0.131-1.522, I2=68.3%; and self-efficacy: β=0.239, 95% CI 0.129-0.349, I2=0.0%), and (3) health status factor (disease: β=-0.177, 95% CI -0.298 to -0.055, I2=26.9%).

CONCLUSIONS: This systematic review, guided by the Literacy and Health Conceptual Framework model, identified key factors influencing eHealth literacy across 3 dimensions: actions (internet usage), determinants (age, ethnicity, income, employment status, education, perceived usefulness, and self-efficacy), and health status (disease). These findings provide valuable guidance for designing interventions to enhance eHealth literacy.

TRIAL REGISTRATION: PROSPERO CRD42022383384; https://www.crd.york.ac.uk/PROSPERO/view/CRD42022383384.

PMID:40063939 | DOI:10.2196/50313

J Med Internet Res. 2025 Mar 10;27:e67188. doi: 10.2196/67188.

ABSTRACT

BACKGROUND: The pursuit of sleep quality has become an important aspect of people’s global quest for overall health. However, the objective neurobiological features corresponding to subjective perceptions of sleep quality remain poorly understood. Although previous studies have investigated the relationship between electroencephalogram (EEG) and sleep, the lack of longitudinal follow-up studies raises doubts about the reproducibility of their findings.

OBJECTIVE: Currently, there is a gap in research regarding the stable associations between EEG data and sleep quality assessed through multiple data collection sessions, which could help identify potential neurobiological targets related to sleep quality.

METHODS: In this study, we used a portable EEG device to collect resting-state prefrontal cortex EEG data over a 3-month follow-up period from 42 participants (27 in the first month, 25 in the second month, and 40 in the third month). Each month, participants’ sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI) to estimate their recent sleep quality.

RESULTS: We found that there is a significant and consistent positive correlation between low α band activity in the prefrontal cortex and PSQI scores (r=0.45, P<.001). More importantly, this correlation remained consistent across all 3-month follow-up recordings (P<.05), regardless of whether we considered the same cohort or expanded the sample size. Furthermore, we discovered that the periodic component of the low α band primarily contributed to this significant association with PSQI.

CONCLUSIONS: These findings represent the first identification of a stable and reliable neurobiological target related to sleep quality through multiple follow-up sessions. Our results provide a solid foundation for future applications of portable EEG devices in monitoring sleep quality and screening for sleep disorders in a broad population.

PMID:40063935 | DOI:10.2196/67188

J Med Internet Res. 2025 Mar 10;27:e64307. doi: 10.2196/64307.

ABSTRACT

BACKGROUND: Effective communication is essential for promoting preventive behaviors during infectious disease outbreaks like COVID-19. While consistent news can better inform the public about these health behaviors, the public may not adopt them.

OBJECTIVE: This study aims to explore the role of different media platforms in shaping public discourse on preventive measures to infectious diseases such as quarantine and vaccination, and how media exposure influences individuals’ intentions to adopt these behaviors in the United States.

METHODS: This study uses data from 3 selected top national newspapers in the United States, Twitter discussions, and a US nationwide longitudinal panel survey from February 2020 to April 2021. We used the Intermedia Agenda-Setting Theory and the Protective Action Decision Model to develop the theoretical framework.

RESULTS: We found a 2-way agenda flow between selected national newspapers and the social media platform Twitter, particularly in controversial topics like vaccination (F_1,426=16.39; P<.001 for newspapers; F_1,426=44.46; P<.001 for Twitter). Exposure to media coverage increased individuals’ perceived benefits of certain behaviors like vaccination but did not necessarily translate into behavioral adoption. For example, while individuals’ media exposure increased perceived benefits of mask-wearing (β=.057; P<.001 for household benefits; β=.049; P<.001 for community benefits), it was not consistently linked to higher intentions to wear masks (β=-.026; P=.04).

CONCLUSIONS: This study integrates media flow across platforms with US national panel survey data, offering a comprehensive view of communication dynamics during the early stage of an infectious disease outbreak. The findings caution against a one-size-fits-all approach in communicating different preventive behaviors, especially where individual and community benefits may not always align.

PMID:40063934 | DOI:10.2196/64307

J Med Internet Res. 2025 Mar 10;27:e51804. doi: 10.2196/51804.

ABSTRACT

BACKGROUND: Google Trends (GT) data have shown promising results as a complementary tool to classical surveillance approaches. However, GT data are not necessarily provided by a representative sample of patients and may be skewed toward demographic and clinical groups that are more likely to use the internet to search for their health.

OBJECTIVE: In this study, we aimed to assess whether GT-based models perform differently in distinct population subgroups. To assess that, we analyzed a case study on asthma hospitalizations.

METHODS: We analyzed all hospitalizations with a main diagnosis of asthma occurring in 3 different countries (Portugal, Spain, and Brazil) for a period of approximately 5 years (January 1, 2012-December 17, 2016). Data on web-based searches on common cold for the same countries and time period were retrieved from GT. We estimated the correlation between GT data and the weekly occurrence of asthma hospitalizations (considering separate asthma admissions data according to patients’ age, sex, ethnicity, and presence of comorbidities). In addition, we built autoregressive models to forecast the weekly number of asthma hospitalizations (for the different aforementioned subgroups) for a period of 1 year (June 2015-June 2016) based on admissions and GT data from the 3 previous years.

RESULTS: Overall, correlation coefficients between GT on the pseudo-influenza syndrome topic and asthma hospitalizations ranged between 0.33 (in Portugal for admissions with at least one Charlson comorbidity group) and 0.86 (for admissions in women and in White people in Brazil). In the 3 assessed countries, forecasted hospitalizations for 2015-2016 correlated more strongly with observed admissions of older versus younger individuals (Portugal: Spearman ρ=0.70 vs ρ=0.56; Spain: ρ=0.88 vs ρ=0.76; Brazil: ρ=0.83 vs ρ=0.82). In Portugal and Spain, forecasted hospitalizations had a stronger correlation with admissions occurring for women than men (Portugal: ρ=0.75 vs ρ=0.52; Spain: ρ=0.83 vs ρ=0.51). In Brazil, stronger correlations were observed for admissions of White than of Black or Brown individuals (ρ=0.92 vs ρ=0.87). In Portugal, stronger correlations were observed for admissions of individuals without any comorbidity compared with admissions of individuals with comorbidities (ρ=0.68 vs ρ=0.66).

CONCLUSIONS: We observed that the models based on GT data may perform differently in demographic and clinical subgroups of participants, possibly reflecting differences in the composition of internet users’ health-seeking behaviors.

PMID:40063932 | DOI:10.2196/51804

J Med Internet Res. 2025 Mar 10;27:e59792. doi: 10.2196/59792.

ABSTRACT

BACKGROUND: Trajectory modeling is a long-standing challenge in the application of computational methods to health care. In the age of big data, traditional statistical and machine learning methods do not achieve satisfactory results as they often fail to capture the complex underlying distributions of multimodal health data and long-term dependencies throughout medical histories. Recent advances in generative artificial intelligence (AI) have provided powerful tools to represent complex distributions and patterns with minimal underlying assumptions, with major impact in fields such as finance and environmental sciences, prompting researchers to apply these methods for disease modeling in health care.

OBJECTIVE: While AI methods have proven powerful, their application in clinical practice remains limited due to their highly complex nature. The proliferation of AI algorithms also poses a significant challenge for nondevelopers to track and incorporate these advances into clinical research and application. In this paper, we introduce basic concepts in generative AI and discuss current algorithms and how they can be applied to health care for practitioners with little background in computer science.

METHODS: We surveyed peer-reviewed papers on generative AI models with specific applications to time-series health data. Our search included single- and multimodal generative AI models that operated over structured and unstructured data, physiological waveforms, medical imaging, and multi-omics data. We introduce current generative AI methods, review their applications, and discuss their limitations and future directions in each data modality.

RESULTS: We followed the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines and reviewed 155 articles on generative AI applications to time-series health care data across modalities. Furthermore, we offer a systematic framework for clinicians to easily identify suitable AI methods for their data and task at hand.

CONCLUSIONS: We reviewed and critiqued existing applications of generative AI to time-series health data with the aim of bridging the gap between computational methods and clinical application. We also identified the shortcomings of existing approaches and highlighted recent advances in generative AI that represent promising directions for health care modeling.

PMID:40063929 | DOI:10.2196/59792

Pol Merkur Lekarski. 2025;53(1):100-107. doi: 10.36740/Merkur202501114.

ABSTRACT

OBJECTIVE: Aim: The research aims to confirm or reject the hypothesis on the possible relationship between the influence of changes in pancreatic vascular variations on the mechanisms of occurrence of pancreatic diseases based on the collected scientific literature..

PATIENTS AND METHODS: Materials and Methods: The bibliosemantic, bibliographic, statistical research methods were used in the research. Scientometric databases Web of Science, Scopus, PubMed, and archives of scientific papers such as Google Scholar and Research Gate for the last 6 years (2018-2023) were used to form a study basis.

CONCLUSION: Conclusions: Based on the analyzed sources, blood supply variants to the pancreas do not influence the development of pathological processes. However, vein and artery features impact treatment choices and surgical outcomes. Main and additional pancreatic ducts, and the common bile duct, may be linked to diseases. Atypical pancreatic artery branching affects surgical tactics and increases bleeding risk.

PMID:40063918 | DOI:10.36740/Merkur202501114

Pol Merkur Lekarski. 2025;53(1):88-93. doi: 10.36740/Merkur202501112.

ABSTRACT

OBJECTIVE: Aim: To investigate the role of thymidine phosphate and IL-6 in the pathogenesis and survival rate in women with breast cancer..

PATIENTS AND METHODS: Materials and Methods: Sixty women diagnosed with breast cancer (with age ranging between 25-65 years) were included in the current study. Of these, 40 women relapse after 6 months of follow up, while 40 patients were non-relapsed.

RESULTS: Results: Statistical analysis pointed out that thymidine phosphorylase may be significantly increased in relapsed women comparing to non-relapsed women (4.48±0.24 ng/ml and 1.12±0.18 ng/ml respectively, p value <0.0001). Regarding IL-6, the current study also found that IL-6 tends to be increased in relapse BC comparing to non-relapsed BC (8.6±0.92 pg/ml vs. 6.82±1.14 pg/ml respectively, p-value<0.0001. There was a high significant positive correlation between thymidine phosphorylase and IL-6 (r=0.368; p-value <0.01). The sensitivity and specificity in predicting relapse in breast cancer were 0.83 and 0.64 for TP and 0.78, and 0.65 respectively.

CONCLUSION: Conclusions: It is suggested that thymidine phosphate activity and IL-6 serum levels after six months of follow up, have a dual synergistic impact on the pathogenesis of relapse for BC. These biomarkers can also be used in the prediction of relapse rate in women diagnosed with BC.

PMID:40063916 | DOI:10.36740/Merkur202501112

Pol Merkur Lekarski. 2025;53(1):81-87. doi: 10.36740/Merkur202501111.

ABSTRACT

OBJECTIVE: Aim: To investigate the impact of the improved Working Program of the academic subject “Special Physical Training” on the dynamics of indicators of cadets’ physical and psycho-emotional state in their training process..

PATIENTS AND METHODS: Materials and Methods: The research, which was conducted in 2023-2024, involved 167 male cadets of the 3rd and 4th training years of National Academy of Internal Affairs (Kyiv, Ukraine). Two groups were formed: the experimental group (EG, n = 86), whose cadets studied according to the improved Working Program of the academic subject area referred to as “Special Physical Training,” and the control group (CG, n = 81), whose cadets studied according to the existing Working Program. Research methods: bibliosemantic, pedagogical experiment, testing, methods of mathematical statistics.

RESULTS: Results: The research found that at the end of the experiment, most of the studied indicators of physical and psycho-emotional state in the EG cadets were significantly better than in the CG cadets. The most pronounced effect of the training sessions with the improved Working Program was found in the indicators of anxiety, neuro-emotional stability, self-confidence, stress resistance, and endurance of future law enforcement officers.

CONCLUSION: Conclusions: A high level of these indicators will ensure the formation of law enforcement officers’ psychophysical readiness for extreme conditions. It will help to improve the efficiency of their performance of service tasks under martial law.

PMID:40063915 | DOI:10.36740/Merkur202501111

Pol Merkur Lekarski. 2025;53(1):12-19. doi: 10.36740/Merkur202501102.

ABSTRACT

OBJECTIVE: Aim: The aim of this study was to investigate and correlate psychosocial risks and musculoskeletal disorders (MSDs) faced by nurses in the hospital work environment..

PATIENTS AND METHODS: Materials and Methods: A cross-sectional study was conducted among 90 nurses (response rate: 56%) working in a General Hospital of Central Greece, from January to March 2023. A self-administered questionnaire was used for data collection, which included demographic information, characteristics of the nursing unit, the Copenhagen Psychosocial Questionnaire Version III (COPSOQ III), and the Nordic Musculoskeletal Questionnaire.

RESULTS: Results: No statistically significant differences were found between individual factors and the COPSOQ scales under examination, except for gender. Professional characteristics, however, were associated with psychosocial risks. For example, an increase in the number of nurses was positively associated with work demands. Conversely, night shifts were negatively associated with freedom of movement, as was the length of employment with opportunities for career development and the assessment of leadership quality. No statistically significant differences were found between MSDs and individual factors. Regarding the correlation between psychosocial risks and MSDs, the study revealed several associations among COPSOQ scales, such as work demands, work-life balance, freedom of movement, social support from colleagues and supervisors, job insecurity and satisfaction, interactions with others, health assessment, and mental exhaustion, with the occurrence of MSDs in body areas such as the neck, shoulders, elbows, wrists, hips, upper back, and ankles.

CONCLUSION: Conclusions: The hospital work environment entails numerous psychosocial risk factors, and ensuring its safety requires their identification and evaluation. Interventions such as ergonomics training, acquiring ergonomic equipment, avoiding manual lifting, and training on the use of patient handling devices can increase risk awareness, reducing the frequency and intensity of musculoskeletal pain.

PMID:40063906 | DOI:10.36740/Merkur202501102