Nevin Manimala

J Med Internet Res. 2025 Feb 26;27:e57730. doi: 10.2196/57730.

ABSTRACT

BACKGROUND: In this era of digitalization, eHealth interventions are used to engage patients in health care and help them manage their health. Previous studies showed that this can be particularly interesting for chronic disease self-management and self-care in older adults. Despite older adults becoming increasingly active on the internet, they continue to struggle in using eHealth information due to inadequate eHealth literacy. Thus, assessing and monitoring eHealth literacy is critical to support eHealth interventions.

OBJECTIVE: This study aimed to describe the translation, adaptation, and validation process of the eHealth Literacy Scale (eHEALS) in Portuguese older adults.

METHODS: The cross-cultural adaption followed the steps of forward and blinded backward translations, evaluation of the translations by a committee of judges, pilot-testing, and full psychometric testing. We tested the psychometric properties of the eHEALS by carrying out two studies: general psychometric analysis (study 1) and confirmatory factor analysis (study 2). Study 1 included 80 older adults conveniently selected from a Health Family Unit. Data were collected by in-person questionnaires between May and July 2022. Study 2 included 301 older adults randomly selected from two distinct Health Family Units. Data were collected by in-person questionnaires between May and July 2023.

RESULTS: We tested stability, reliability, construct validity (exploratory and confirmatory factor analyses and known groups), and model fit. Study 1 had 58.8% (47/80) male and 41.3% (33/80) female respondents (mean age 71.20, SD 5.26 years). Study 2 had 56.5% (170/301) male and 43.5% (131/301) female respondents (mean age 71.77, SD 5.15 years). Moderate and strong correlations were identified in the scale items (study 1: 0.42≤r≤0.91 and study 2: 0.81≤r≤0.96; P<.001). The scale showed good internal consistency for study 1 (α=.92) and study 2 (α=.98), with high correlations between items. The exploratory factor analysis yielded a single-factor structure, explaining 58.3% of the variance in study 1 and 86.4% in study 2. In the confirmatory analysis (study 2), the model fit was mixed (χ²₂₀=265, P<.001; comparative fit index=0.94; Tucker-Lewis Index=0.91; root mean square error of approximation=0.20). Thus, we compared 1-, 2-, and 3-factor structures, deciding on the unidimensional one. In study 1, the eHEALS-PT24 (Portuguese version of the eHealth Literacy Scale for older adults) mean score was 27.25 (SD 5.61), with 43.8% (35/80) and 11.3% (9/80) of participants showing low and high eHealth literacy levels, respectively. In study 2, the eHEALS-PT24 mean score was 23.31 (SD 9.53), with 38.2% (115/301) and 23.6% (71/301) of participants showing low and high eHealth literacy levels, respectively. The known-groups analysis showed statistically significant differences between eHealth literacy and demographic variables (P<.001).

CONCLUSIONS: The findings suggest that the eHEALS-PT24 is a reliable and valid tool to assess eHealth literacy in Portuguese older adults. Therefore, this instrument can be integrated to support the implementation process of eHealth interventions.

PMID:40009846 | DOI:10.2196/57730

JMIR Res Protoc. 2025 Feb 26;14:e51502. doi: 10.2196/51502.

ABSTRACT

BACKGROUND: Optimal anticoagulation using vitamin K antagonists prevents strokes associated with atrial fibrillation and heart valve replacements. Preparedness for self-monitoring and self-management could improve outcomes, but this remains a challenge.

OBJECTIVE: This study aimed to outline the methodology for developing and validating the PERSONAE scale, a self-report measure designed to assess the preparedness for self-monitoring and self-management of oral anticoagulation in adult patients.

METHODS: This study comprises 2 main phases, and it adheres to the “COnsensus-based Standards for the selection of health Measurement INstruments” (COSMIN) guidelines for instrument development. The first phase involved the conceptualization of the PERSONAE scale, where a comprehensive literature review and a consensus meeting among experts were conducted to draft the initial items. Face and content validity were then established through an expert panel review. In the second phase (ongoing), a detailed sampling methodology will be used, targeting adult Italian patients on long-term oral anticoagulation. According to a performed simulation-based power analysis, the study aims to recruit a sample size of approximately 500 participants by using a combination of convenience and snowball sampling. Data collection will be facilitated through web-based surveys distributed through social media and patient networks, ensuring a wide and representative sample. Analytical procedures will include Mokken scaling analysis for item selection and confirmatory factor analysis to validate the scale’s structure. In addition, internal consistency will be assessed using Molenaar Sijtsma statistics.

RESULTS: The scale’s content derived from phase 1 (process completed in December 2023) is grounded in a comprehensive literature review and based on the assessments of a panel of 12 health care expert professionals. The PERSONAE scale derived from phase 1 encompasses 20 items reflecting essential behaviors needed to assess the preparedness for self-monitoring and self-management of oral anticoagulation. Each item obtained a content validity ratio higher than 0.67, which is the critical content validity ratio indicating the minimum level of agreement among the experts for an item to be considered essential beyond the level of chance at a significance level of .05 for a 1-tailed test. From January 2024 to May 2024, we conducted the initial round of data collection and use Mokken scaling analysis to select items. A second round of data collection for confirmatory factor analysis was scheduled from June 2024 to September 2024, which will validate the scale’s unidimensional structure. We expect to achieve robust psychometric properties, including high internal consistency and validated constructs.

CONCLUSIONS: The PERSONAE scale will be a valuable tool to assess patients’ preparedness for self-monitoring and self-management of oral anticoagulation. The study’s insights into technology-assisted learning preferences will inform the design of future educational interventions to enhance preparedness in adult patients.

TRIAL REGISTRATION: ClinicalTrials.gov NCT05973240; https://clinicaltrials.gov/study/NCT05973240.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/51502.

PMID:40009845 | DOI:10.2196/51502

JMIR Aging. 2025 Feb 26;8:e64148. doi: 10.2196/64148.

ABSTRACT

BACKGROUND: The atherosclerotic cardiovascular disease (ASCVD) is associated with dementia. However, the risk factors of dementia in patients with ASCVD remain unclear, necessitating the development of accurate prediction models.

OBJECTIVE: The aim of the study is to develop a machine learning model for use in patients with ASCVD to predict dementia risk using available clinical and sociodemographic data.

METHODS: This prognostic study included patients with ASCVD between 2006 and 2010, with registration of follow-up data ending on April 2023 based on the UK Biobank. We implemented a data-driven strategy, identifying predictors from 316 variables and developing a machine learning model to predict the risk of incident dementia, Alzheimer disease, and vascular dementia within 5, 10, and longer-term follow-up in patients with ASCVD.

RESULTS: A total of 29,561 patients with ASCVD were included, and 1334 (4.51%) developed dementia during a median follow-up time of 10.3 (IQR 7.6-12.4) years. The best prediction model (UK Biobank ASCVD risk prediction model) was light gradient boosting machine, comprising 10 predictors including age, time to complete pairs matching tasks, mean time to correctly identify matches, mean sphered cell volume, glucose levels, forced expiratory volume in 1 second z score, C-reactive protein, forced vital capacity, time engaging in activities, and age first had sexual intercourse. This model achieved the following performance metrics for all incident dementia: area under the receiver operating characteristic curve: mean 0.866 (SD 0.027), accuracy: mean 0.883 (SD 0.010), sensitivity: mean 0.637 (SD 0.084), specificity: mean 0.914 (SD 0.012), precision: mean 0.479 (SD 0.031), and F₁-score: mean 0.546 (SD 0.043). Meanwhile, this model was well-calibrated (Kolmogorov-Smirnov test showed goodness-of-fit P value>.99) and maintained robust performance across different temporal cohorts. Besides, the model had a beneficial potential in clinical practice with a decision curve analysis.

CONCLUSIONS: The findings of this study suggest that predictive modeling could inform patients and clinicians about ASCVD at risk for dementia.

PMID:40009844 | DOI:10.2196/64148

Interact J Med Res. 2025 Feb 26;14:e66286. doi: 10.2196/66286.

ABSTRACT

BACKGROUND: Ferroptosis, as a novel modality of cell death, holds significant potential in elucidating the pathogenesis and advancing therapeutic strategies for breast cancer.

OBJECTIVE: This study aims to comprehensively analyze current ferroptosis research and future trends, guiding breast cancer research advancements and innovative treatment strategies.

METHODS: This research used the R package Bibliometrix (Department of Economic and Statistical Sciences at the University of Naples Federico II), VOSviewer (Centre for Science and Technology Studies at Leiden University), and CiteSpace (Drexel University’s College of Information Science and Technology), to conduct a bibliometric analysis of 387 papers on breast cancer and ferroptosis from the Web of Science Core Collection. The analysis covers authors, institutions, journals, countries or regions, publication volumes, citations, and keywords.

RESULTS: The number of publications related to this field has surged annually, with China and the United States collaborating closely and leading in output. Sun Yat-sen University stands out among the institutions, while the journal Frontiers in Oncology and the author Efferth T contribute significantly to the field. Highly cited papers within the domain primarily focus on the induction of ferroptosis, protein regulation, and comparisons with other modes of cell death, providing a foundation for breast cancer treatment. Keyword analysis highlights the maturity of glutathione peroxidase 4-related research, with breast cancer subtypes emerging as motor themes and the tumor microenvironment, immunotherapy, and prognostic models identified as basic themes. Furthermore, the application of nanoparticles serves as an additional complement to the basic themes.

CONCLUSIONS: The current research status in the field of ferroptosis and breast cancer primarily focuses on the exploration of relevant theoretical mechanisms, whereas future trends and mechanisms emphasize the investigation of therapeutic strategies, particularly the clinical application of immunotherapy related to the tumor microenvironment. Nanotherapy has demonstrated significant clinical potential in this domain. Future research directions should deepen the exploration in this field and accelerate the clinical translation of research findings to provide new insights and directions for the innovation and development of breast cancer treatment strategies.

PMID:40009842 | DOI:10.2196/66286

J Med Internet Res. 2025 Feb 26;27:e55492. doi: 10.2196/55492.

ABSTRACT

BACKGROUND: Sepsis is an organ dysfunction caused by a dysregulated host response to infection. Early detection is fundamental to improving the patient outcome. Laboratory medicine can play a crucial role by providing biomarkers whose alteration can be detected before the onset of clinical signs and symptoms. In particular, the relevance of monocyte distribution width (MDW) as a sepsis biomarker has emerged in the previous decade. However, despite encouraging results, MDW has poor sensitivity and positive predictive value when compared to other biomarkers.

OBJECTIVE: This study aims to investigate the use of machine learning (ML) to overcome the limitations mentioned earlier by combining different parameters and therefore improving sepsis detection. However, making ML models function in clinical practice may be problematic, as their performance may suffer when deployed in contexts other than the research environment. In fact, even widely used commercially available models have been demonstrated to generalize poorly in out-of-distribution scenarios.

METHODS: In this multicentric study, we developed ML models whose intended use is the early detection of sepsis on the basis of MDW and complete blood count parameters. In total, data from 6 patient cohorts (encompassing 5344 patients) collected at 5 different Italian hospitals were used to train and externally validate ML models. The models were trained on a patient cohort encompassing patients enrolled at the emergency department, and it was externally validated on 5 different cohorts encompassing patients enrolled at both the emergency department and the intensive care unit. The cohorts were selected to exhibit a variety of data distribution shifts compared to the training set, including label, covariate, and missing data shifts, enabling a conservative validation of the developed models. To improve generalizability and robustness to different types of distribution shifts, the developed ML models combine traditional methodologies with advanced techniques inspired by controllable artificial intelligence (AI), namely cautious classification, which gives the ML models the ability to abstain from making predictions, and explainable AI, which provides health operators with useful information about the models’ functioning.

RESULTS: The developed models achieved good performance on the internal validation (area under the receiver operating characteristic curve between 0.91 and 0.98), as well as consistent generalization performance across the external validation datasets (area under the receiver operating characteristic curve between 0.75 and 0.95), outperforming baseline biomarkers and state-of-the-art ML models for sepsis detection. Controllable AI techniques were further able to improve performance and were used to derive an interpretable set of diagnostic rules.

CONCLUSIONS: Our findings demonstrate how controllable AI approaches based on complete blood count and MDW may be used for the early detection of sepsis while also demonstrating how the proposed methodology can be used to develop ML models that are more resistant to different types of data distribution shifts.

PMID:40009841 | DOI:10.2196/55492

JMIR Hum Factors. 2025 Feb 26;12:e58362. doi: 10.2196/58362.

ABSTRACT

BACKGROUND: Telehealth is an increasingly important component of health care services. Telehealth services may present an opportunity to increase the equity, accessibility, and effectiveness of health care. As such, it is critical that telehealth design focuses on reducing the barriers to access and usability that may impair some telehealth users.

OBJECTIVE: Our goal was to identify different demographic characteristics, behaviors, or opinions that may predict groups who are likely to face a barrier to using telehealth services.

METHODS: We used data from the National Health Interview Survey and multiple logit regression models focused on different aspects of telehealth to examine three different avenues of telehealth service: looking up health information using the internet, scheduling an appointment using the internet, and communicating with a care provider through email using the internet in order to consider the ways in which different telehealth services may face different barriers.

RESULTS: Our results suggest that middle-aged (36-55 years old) and older adult (56-85 years old) respondents were significantly less likely to look up health information using the internet or schedule an appointment using the internet versus younger individuals (18-35 years old). Specifically, our analysis found that middle-aged adults were found to have a higher odds ratio than older adults (0.83 vs 0.65) for looking up health information using the internet. We also found that there were differences in age groups for using technology to perform health care-related tasks. In terms of searching for health information using the internet and scheduling appointments using the internet, we found differences between men and women, with women being significantly more likely than men to look up health information using the internet, schedule an appointment using the internet, and communicate with a care provider through email using the internet. Across all the investigated variables, we found that the rates of using the internet for looking up health information, scheduling an appointment, and communicating with a care provider over email increased substantially across the study period. The impact of costs was inconsistent across the different models in our analysis. We also found that there is a strong correlation between respondents’ collaboration in their personal health and the likelihood that they would use telehealth services to meet these needs.

CONCLUSIONS: This analysis provides an exploratory look at the data to highlight barriers that may impact a user’s ability to access telehealth services in the context of other potential predictor variables to account for the real-world variability that these may present. Future work should examine the complex relationships of those variables and understand how these interactions are correlated with the respondents’ use of telehealth.

PMID:40009837 | DOI:10.2196/58362

J Med Internet Res. 2025 Feb 26;27:e65092. doi: 10.2196/65092.

ABSTRACT

BACKGROUND: China has changed its COVID-19 prevention and control status since 2023. However, what role telemedicine will play post-COVID-19 is still uncertain.

OBJECTIVE: We aimed to determine the frequency change in health care providers offering telemedicine services before, during, and after COVID-19, as well as the correlation between the frequency change and telemedicine visit time.

METHODS: The Telemedicine Informationization Professional Committee of China (TIPC) carried out a nationwide questionnaire survey. We adopted data from part of the questionnaires that answered questions regarding the frequency of offering telemedicine services before, during, and after the COVID-19 explosion. Chi-square tests were applied to compare general differences in the between-group telemedicine frequency. Regression models were performed to analyze correlations between the frequency change and the time spent in online versus in-person visits.

RESULTS: Questionnaires from 428 providers were included. As reported, 39 (9.11%) providers often and 159 (37.15%) always offered telemedicine services before COVID-19 exploded. The component ratio increased to 12.38% (n=53) of providers often and 45.79% (n=196) always offering telemedicine during COVID-19 explosion and 12.62% (n=54) often and 50% (n=214) always offering telemedicine after pandemic control was relaxed. The increase in frequency shown as a difference between the before and during groups (χ2=17.21, P.002) and between the before and after groups (χ2=30.17, P<.001) was significant, while it was insignificant between the during and after groups (χ2=2.89, P.57). Senior professional titles (odds ratio [OR] 4.38, 95% CI 1.72-11.6) and longer (OR 3.87, 95% CI 1.95-7.89) and shorter (OR 2.04, 95% CI 1.11-3.87) online visits were correlated with the increase in frequency during versus before COVID-19. In addition, senior professional titles (OR 3.47, 95% CI 1.46-8.49), longer (OR 3.14, 95% CI 1.64-6.11) and shorter (OR=2.27, 95% CI 1.31-4.07) online visits, and using third-party telemedicine platforms (OR 0.51, 95% CI 0.29-0.86) were correlated with the increase in frequency after versus before COVID-19. No factor was significantly correlated with the frequency change after versus during COVID-19. In stratified analysis, longer online visits were correlated with both during versus before (OR 3.84, 95% CI 1.73-8.83) and after versus before (OR 3.40, 95% CI 1.61-7.34) groups for providers using hospital-run platforms, while shorter online visits were correlated with both during versus before (OR 8.16, 95% CI 1.39-68.3) and after versus before (OR 5.70, 95% CI 1.22-33.6) groups for providers using third-party platforms.

CONCLUSIONS: The frequency of telemedicine has increased since the COVID-19 pandemic exploded and is correlated with the time spent in online versus in-person visits. The correlation is different for providers using hospital-run and third party platforms. On a hospital-run platform, providers with longer online visits have a higher frequency of offering telemedicine, while on a third-party platform, providers with shorter online visits are more likely to offer telemedicine.

PMID:40009835 | DOI:10.2196/65092

West Afr J Med. 2024 Oct 30;41(10):1028-1033.

ABSTRACT

BACKGROUND: Colonoscopy remains the gold standard for examining and detecting lesions of the colon and can be used as a therapeutic procedure.

AIM: To report our colonoscopy experience in a private hospital in Nigeria.

PATIENTS AND METHODS: This was a retrospective review of all consecutive patients who underwent colonoscopy from September 2020 to January 2022 (17 months) at Saint Nicholas hospital, a private hospital in Lagos, Nigeria. Informed consents for colonoscopy were obtained from all the patients recruited. Ethical approval for the publication of this manuscript was obtained from the Hospital authority. Each patient had a 3-day bowel preparation before the procedure. Statistical analysis was carried out using IBM SPSS version 26.

RESULTS: A total of one hundred and one patients were recruited into the study with no exclusion. There were 68 males and 33 females with a male to female ratio of 2:1. The mean age of the patients was 52.2± 1.4 years with age range of 23-93 years. The most common indication for colonoscopy was bleeding per rectum. Caecal intubation was achieved in 97% of the patients. Normal findings were recorded in 71% of the patients.

CONCLUSION: The most common indication for colonoscopy was bleeding per rectum. Caecal intubation was achieved in the majority of the patients with the colon noted to be normal in over two-thirds of the patients.

PMID:40009832

West Afr J Med. 2024 Oct 30;41(10):1023-1027.

ABSTRACT

AIM: To report the relationship between average keratometric (AK) readings and axial length (AL) measurements in left eyes of patients attending a cataract surgery camp in sub-Saharan Africa.

METHODS: A prospective evaluation of 648 left eyes of consecutive patients who presented for a cataract surgery camp. The KOWA Autorefractor and Alcon ocuscan were used for measurements. Left eyes alone were evaluated to reduce duplication of data. The data obtained were statistically analyzed using Statistical Package for Social Sciences, version 20.0 (SPSS v20).

RESULTS: A total of 648 eyes of 648 patients were analyzed. There were 306 (47.2%) males and 342 (52.8%) females with age range from 11 to 95 years, mean ± SD age of 65.70 ± 14.28 years. AL range was from 18.00 mm to 30.39 mm, mean ± SD of 23.21± 1.19. AK ranged from 38.50 D to 48.50 D with mean ± SD of 43.41±1.68. AK reading of patients’ left eye increased as the patients age increased (p=0.007). AK readings also increased with a reduction in AL (p=<0.001). Hence smaller eyes had steeper corneas. AL of left eye and AK readings were linearly related by: AL = 33.29 – 0.232AK.

CONCLUSION: Average keratometric readings in left eyes of our cohort of patients increased with age (p=0.007) and reducing axial length (p=<0.001). Axial length of left eye and Average-K readings are linearly related by: AL = 33.29 – 0.232AK. This formula can be utilized during cataract camps to estimate either value, used in intraocular lens calculations.

PMID:40009825

West Afr J Med. 2024 Oct 30;41(10):1015-1022.

ABSTRACT

BACKGROUND: Magnesium has been shown to attenuate succinylcholine-induced fasciculation (SIF) and postoperative muscle pain (POMP); however, the optimal dose remains undetermined. This study explores the effects of varying low doses in a Nigerian population.

METHODS: Ninety patients, aged 18 and 65 years, ASA I and II, who had succinylcholine-assisted airway management, under general anaesthesia, (with propofol-midazolam co-induction, isoflurane and pancuronium maintenance), were randomised into three groups. All patients received magnesium pretreatment before induction; group A received 7.5mg/kg, group B received 10 mg/kg, while group C received 20 mg/kg.

RESULTS: Socio-demographic characteristics were comparable in all groups, p-value > 0.05. The overall incidence of SIF was similar between groups A (24, 80.0%) and B (22, 73.3%), and significantly higher than group C (12, 40.0%) (p = 0.001). Incidence of mild SIF were similar between groups A, (13, 43.3%) and B, (16, 53.3%), and statistically lesser than C, (12, 40.0%), p-value 0.001. The overall POMP incidence was similar between group A, (15, 50.0%) and B, (14, 46.7%), and statistically higher than C, (6, 20.0%), p-value 0.021.

CONCLUSION: This study demonstrates that a 20 mg/kg magnesium pretreatment attenuates SIF and POMP more effectively than 7.5 mg/kg and 10 mg/kg doses in patients undergoing succinylcholine-assisted airway management for general anesthesia.

PMID:40009802