Category: Nevin Manimala

JMIR Form Res. 2025 May 16;9:e60294. doi: 10.2196/60294.

ABSTRACT

BACKGROUND: In recent times, the telemedicine landscape has changed dramatically; it serves as a bridge, connecting health care providers and patients, especially during challenges such as the recent COVID-19 pandemic.

OBJECTIVE: This study seeks to explore the Swedish telemedicine landscape in terms of primary patient symptoms for teleconsultation and the patterns of telemedicine use in the periods before COVID-19, during COVID-19, and after COVID-19, including the primary care use dynamics with respect to the teleconsultations done.

METHODS: Secondary data was used in this observational retrospective study. The study population consisted of Swedish residents who had online telemedicine consultations. Telemedicine consultations were divided by text and video delivery; the period of analysis ranged from November 2018 to June 2023. The statistical methods used for the data analysis were descriptive analysis, 2-way cross tabulation, and a generalized linear model.

RESULTS: During the pandemic, the number of teleconsultations concerning general, unspecified symptoms increased in comparison to the other analyzed symptoms, signaling a change in care-seeking behavior under epidemiological pressure. General health-related issues were the most pronounced symptom across all periods: 186.9 of 1000 consultations before COVID-19, 1264.6 of 1000 consultations during COVID-19, and 319.2 of 1000 consultations after COVID-19. There was no significant main effect of COVID-19 period on the number of telemedicine consultation meetings (F2=1.653; P=.38). The interaction effect between delivery type and period was statistically significant (F2=14.723; P<.001).

CONCLUSIONS: The findings are in favor of the COVID-19 pandemic having had a considerable effect on telemedicine use. Telemedicine could subsequently be used more often for general health consultations and acute conditions. Video consultations were more prominent because of the importance of bidirectional communication. The study suggests that there was a transformation of patterns of demand for health care; there is a necessity for health care systems to respond to these changes.

PMID:40378415 | DOI:10.2196/60294

JMIR Form Res. 2025 May 16;9:e70104. doi: 10.2196/70104.

ABSTRACT

BACKGROUND: Fruit and vegetable consumption is lower than national trends among people receiving Supplemental Nutrition Assistance Program (SNAP) benefits due to economic and physical access barriers. Monetary nutrition incentive programs at farmers markets aim to reduce these barriers to improve diet quality among SNAP consumers. We leveraged community-engaged methods to collaboratively design a mobile app to increase the use of both nutrition incentive programs and farmers markets among SNAP households with children. This population represents about 35% of all SNAP households providing the dual benefit of improving diet for both adults and children.

OBJECTIVE: In this paper, we share the iterative, community-engaged development process used to design a technology intervention that encourages the integration of farmers markets into the food shopping routines of SNAP consumers with children.

METHODS: Our qualitative community-engaged approach was informed by human-centered design, following the inspiration and ideation phases of this framework. In the “inspiration” phase, we worked with community nutrition experts to define both the goal of and target audience for the app (ie, SNAP households with children). In the subsequent “ideation” phase, we completed 3 stages of data collection. We developed 2 interface prototypes and received feedback from end users on design and usability preferences before selecting a baseline model. Additional feedback gathered from qualitative interviews with 20 SNAP consumers with children was incorporated into the app’s version 1 (V1) development. We then shared V1 with SNAP consumers, children, and farmers market managers to test the app’s functionality, design, and utility.

RESULTS: In the “inspiration” phase, the community nutrition partners identified SNAP consumers with children younger than 18 years as the target population for the app. In the “ideation” phase, we successfully created V1 through 3 stages of a qualitative, community-engaged process. First, about 75% (n=3) of SNAP consumers and all farmers market managers selected a grocery shopping design option for the layout of the app. Second, we integrated features identified by SNAP consumers with children into the app design, such as market information (ie, location with GPS address links, hours, website), likely available market inventory, market events, and grocery shopping checklists. Finally, we obtained recommendations for future versions of the app, including real-time changes in market hours, additional notification options, and grocery list personalization during a demonstration of V1. Both SNAP consumers and farmers market managers expressed interest in the app’s launch and utility.

CONCLUSIONS: It is feasible for community nutrition researchers to successfully design a community-engaged mobile app with the assistance of software developers. The community-engaged approach was key to us integrating potential end users’ preferences in the design of V1. Future work will assess the app’s impact on low-income families’ use of local farmers markets and nutrition incentive programs, as well as fruit and vegetable consumption.

PMID:40378408 | DOI:10.2196/70104

JMIR Aging. 2025 May 16;8:e67267. doi: 10.2196/67267.

ABSTRACT

BACKGROUND: Cognitive training for older adults is crucial before cognitive impairment emerges. During periods of social distancing like the COVID-19 pandemic, cognitive stimuli are lacking. Online dual-task training is proposed as a solution to address these needs.

OBJECTIVE: We aimed to explore the feasibility, acceptance, and potential effects of online group-based dual-task training as an intervention for enhancing cognitive function among community-dwelling older adults.

METHODS: A randomized controlled feasibility study was conducted with 76 participants in Hong Kong, randomly assigned to the intervention and attention control groups in a ratio of 2:1 (n=50, 66% and n=26, 34%, respectively). The intervention group underwent 60-minute online dual-task training sessions twice a week for 12 weeks, incorporating cognitive components (upper limb and finger movement, arithmetic operation, and verbal fluency) and physical components (chair-based exercises) developed through a co-design approach. The attention control group received online health talks. Outcomes related to feasibility and acceptance included class attendance and self-reported satisfaction. Main outcomes related to potential effects included the Memory Inventory in Chinese and the Montreal Cognitive Assessment 5 Minutes (Hong Kong Version) at baseline, 6 weeks (midintervention), 12 weeks (postintervention) and 18 weeks (follow-up). Descriptive statistics and linear mixed effects models were used. Effect size was described with Cohen d. Qualitative feedback was collected from 12 informants and analyzed by thematic analysis.

RESULTS: About 72% (36/50) of the participants in the intervention group and 62% (16/26) in the control group attended over 75% of the classes. In total, 44 (88%) participants from the intervention group provided acceptance feedback; 82% (36/44) were satisfied and 84% (37/44) would recommend the training to others. Improvement in the Memory Inventory in Chinese score in the intervention group was observed at midintervention, postintervention, and follow-up, with a medium-to-large effect size (d=0.65, 0.43 and 0.85, respectively). Adjusting for baseline values, the between-group differences in the Montreal Cognitive Assessment 5 Minutes (Hong Kong Version) score attained a small-to-medium effect size at midintervention (d=0.34) and postintervention (d=0.23). Qualitative feedback highlighted the timesaving and convenient aspects of online dual-task training, with participants finding the sessions challenging and enjoyable, and reporting benefits across cognitive, physical, and psychosocial domains. However, a preference for traditional in-person training was noted among the older adults despite the advantages of online training.

CONCLUSIONS: Online dual-task training is a feasible intervention accepted by the older adults, with potential benefits in cognitive abilities. Online training may complement in-person sessions. Further investigation in a full-scale randomized controlled trial is warranted to comprehensively explore its effects and address areas for improvement.

TRIAL REGISTRATION: ClinicalTrials.gov NCT05573646; https://clinicaltrials.gov/study/NCT05573646.

PMID:40378407 | DOI:10.2196/67267

JMIR Med Inform. 2025 May 16;13:e66917. doi: 10.2196/66917.

ABSTRACT

BACKGROUND: The capabilities of large language models (LLMs) to self-assess their own confidence in answering questions within the biomedical realm remain underexplored.

OBJECTIVE: This study evaluates the confidence levels of 12 LLMs across 5 medical specialties to assess LLMs’ ability to accurately judge their own responses.

METHODS: We used 1965 multiple-choice questions that assessed clinical knowledge in the following areas: internal medicine, obstetrics and gynecology, psychiatry, pediatrics, and general surgery. Models were prompted to provide answers and to also provide their confidence for the correct answers (score: range 0%-100%). We calculated the correlation between each model’s mean confidence score for correct answers and the overall accuracy of each model across all questions. The confidence scores for correct and incorrect answers were also analyzed to determine the mean difference in confidence, using 2-sample, 2-tailed t tests.

RESULTS: The correlation between the mean confidence scores for correct answers and model accuracy was inverse and statistically significant (r=-0.40; P=.001), indicating that worse-performing models exhibited paradoxically higher confidence. For instance, a top-performing model-GPT-4o-had a mean accuracy of 74% (SD 9.4%), with a mean confidence of 63% (SD 8.3%), whereas a low-performing model-Qwen2-7B-showed a mean accuracy of 46% (SD 10.5%) but a mean confidence of 76% (SD 11.7%). The mean difference in confidence between correct and incorrect responses was low for all models, ranging from 0.6% to 5.4%, with GPT-4o having the highest mean difference (5.4%, SD 2.3%; P=.003).

CONCLUSIONS: Better-performing LLMs show more aligned overall confidence levels. However, even the most accurate models still show minimal variation in confidence between right and wrong answers. This may limit their safe use in clinical settings. Addressing overconfidence could involve refining calibration methods, performing domain-specific fine-tuning, and involving human oversight when decisions carry high risks. Further research is needed to improve these strategies before broader clinical adoption of LLMs.

PMID:40378406 | DOI:10.2196/66917

J Med Internet Res. 2025 May 16;27:e62661. doi: 10.2196/62661.

ABSTRACT

BACKGROUND: The escalating prevalence of obesity worldwide increases the risk of chronic diseases and diminishes life expectancy, with a growing economic burden necessitating urgent intervention. The existing tiered approach to weight management, particularly specialist tier 3 services, falls short of meeting the population’s needs. The emergence of digital health tools, while promising, remains underexplored in specialized National Health Service weight management services (WMSs).

OBJECTIVE: This service evaluation study assessed the use, effectiveness, and clinical impact of the W8Buddy digital support tool as part of the National Health Service WMS.

METHODS: W8Buddy, a personalized digital platform, provides a tailored weight management plan to empower individuals and was collaboratively developed with input from patients, the clinical team, and DDM Health. It launched at the University Hospitals Coventry and Warwickshire tier 3 WMS in 2022. All patients accessing University Hospitals Coventry and Warwickshire WMS were offered W8Buddy as part of standard care. Data were analyzed using independent samples t tests and Fisher exact tests for continuous and categorical outcomes, respectively. Multiple linear regression analysis explored associations between participant weight, engagement with W8Buddy, and time in the service.

RESULTS: Complete datasets for weights were available for 421 patients (220 W8Buddy group and 192 nonuser control group). W8Buddy users, predominantly female (n=185, 84.1%) and Caucasian, had a mean age of 43 years, while nonusers averaged 46 years (P=.02). Starting weights were comparable: 134 kg in the W8Buddy group and 130.2 kg in controls (P=.14); however, W8Buddy users had slightly higher starting BMI (49.6 vs 46.8 kg/m², P=.08). A total of 33.5% (n=392) of patients activated W8Buddy and engaged with it. There was significant weight loss among W8Buddy users, with a 0.74 kg monthly loss compared to standard care (β=-.74, 95% CI -1.28 to -0.21; P=.007). The longer an individual stayed in this study and used W8Buddy, the more weight was lost. W8Buddy users with type 2 diabetes mellitus experienced a significant hemoglobin A_1c reduction (59.8 to 51.2 mmol/mol, P=.02) compared to nonusers with type 2 diabetes. W8Buddy users also showed significant improvement across the Satisfaction With Life Scale, the Karolinska Sleepiness Scale, and quality of life visual analog scale (P<.001) during follow-up.

CONCLUSIONS: Participants engaging with W8Buddy as part of a digitally enabled tier 3 WMS demonstrated significant improvements in clinical and psychological outcomes, with weight changes statistically significant compared to those not engaging with the digital tool. Reduction in hemoglobin A_1c was present in both groups; however, statistical significance was only reached among those engaging with W8Buddy. These findings suggest digital tools can augment traditional services and promote patient empowerment. Future studies must provide long-term data to understand if the benefits from the digital tool are sustained.

PMID:40378402 | DOI:10.2196/62661

PLoS One. 2025 May 16;20(5):e0322623. doi: 10.1371/journal.pone.0322623. eCollection 2025.

ABSTRACT

Community-acquired pneumonia (CAP) is a major cause of hospitalization that leads to substantial morbidity, mortality, and costs. Evaluating CAP trends over time is important to understand patterns and the impact of public health interventions. This study aims to describe the characteristics and trends in the incidence of adults hospitalized with CAP in Portugal between 2010 and 2018. In this study, we included hospitalization data, prevalence of comorbidities, and population data. CAP hospitalizations of adults (≥18y) living in mainland Portugal discharged from public hospitals were identified using ICD-9-CM or ICD-10-CM codes. Based on previous CAP studies, we selected nine relevant comorbidities. We described the frequency and incidence of CAP hospitalizations per sex, age group, comorbidity, and year of discharge. Trends were explored using Joinpoint regression. We observed 470,545 CAP hospitalizations falling into the 2010-18 period. The majority were males (54.8%) and aged ≥75 years (65.3%). Most often recorded comorbidities were congestive heart failure (26.4%), diabetes (25.5%), and chronic pulmonary disease (19.2%). The Joinpoint regression identified a gradual decline in the incidence rates of CAP hospitalizations for both sexes and all age groups. Of the nine comorbidities selected, seven showed a progressive increase in incidence rates followed by a subsequent decline (all except HIV/AIDS and chronic renal disease). Our findings offer valuable insights for selecting priority groups for public health interventions and design strategies to mitigate the burden of CAP.

PMID:40378392 | DOI:10.1371/journal.pone.0322623

PLoS One. 2025 May 16;20(5):e0323834. doi: 10.1371/journal.pone.0323834. eCollection 2025.

ABSTRACT

BACKGROUND: A growing body of research indicates that sex (biological) and gender (sociocultural) influence health through a variety of distinct mechanisms. Sex- and Gender-Based Analysis (SGBA) techniques could examine these influences, however, there is a lack of nuanced and easily implementable measurement tools for health research. To address this gap, we created the Sex- and Gender-Based Analysis Tool – 5 item (SGBA-5).

OBJECTIVES: This research aims to assess the validity and reliability of the SGBA-5 for use in health sciences research where sex or gender are not primary variables of interest.

METHODS: A Delphi consensus study was conducted with Canadian researchers (n = 14). The Delphi experts rated the validity of each SGBA-5 item on a 5-point Likert scale each round, receiving summary statistics of other experts’ responses after the first round. A conservative threshold for consensus agreement (75% rating an item 4+ of 5) was used given the novelty of this scale’s items. Reliability was assessed through a two-armed test-retest study. The university student arm (n = 89) was conducted in-person (on paper), and the older adult arm (n = 71) was conducted online (digitally).

RESULTS: The Delphi study ended after three rounds; experts reached consensus agreement on the validity of the biological sex item of the SGBA-5 (93%) and consensus non-agreement on each of the gendered aspect of health items (identity: 64%, expression: 64%, roles: 50%, relations: 57%). Both the student arm (sex item: [Formula: see text], gendered items: [Formula: see text]) and the older adult arm (sex item: [Formula: see text], gendered items: [Formula: see text]) of the test-retest study indicated that all items were reliable.

CONCLUSIONS: The novel SGBA-5 tool demonstrated reliability across all scale items and validity of the biological sex item. The gendered aspects of health items may be valid. Future research can further develop the SGBA-5 as a tool for use in health research.

PMID:40378387 | DOI:10.1371/journal.pone.0323834

PLoS One. 2025 May 16;20(5):e0323139. doi: 10.1371/journal.pone.0323139. eCollection 2025.

ABSTRACT

BACKGROUND/OBJECTIVES: The prevalence of hepatitis A virus (HAV) is associated with socioeconomic conditions, access to clean drinking water, and improvements in sanitation. In Vietnam, epidemiological data on HAV have been limited over the past two decades. This study aims to assess age-specific HAV seroprevalence across two distinct geographic regions, urban and rural areas, and identify the risk factors associated with HAV seropositivity in Vietnam.

METHODS: This cross-sectional seroprevalence study was conducted in two distinct areas in Vietnam. Serological testing for anti-HAV total antibodies was performed, and socio-demographic questionnaires were administered to all participants. The age at the midpoint of population immunity (AMPI) was calculated and analyzed.

RESULTS: A total of 1,281 participants aged 1-80 years were included, with 649 from urban areas and 632 from rural areas. Of the total participants, 33.2% were aged <15 years. Overall, HAV seropositivity was 69.2%, with urban areas exhibiting significantly lower seropositivity (57.9%) compared to rural areas (80.7%) (p < 0.001). The AMPI was 29 years, indicating Vietnam is at intermediate HAV endemicity. Multivariate analysis identified key risk factors for HAV infection, including age and rural residence. Conversely, participants with higher educational levels and those who consumed boiled drinking water were less likely to be HAV seropositive.

CONCLUSIONS: The study identified significant differences in the HAV seroprevalence between urban and rural areas, providing critical data for public health officials. These findings highlight the key role of targeted public health interventions and vaccination programs in mitigating HAV infection rates and reducing the disease burden, particularly among high-risk populations in Vietnam.

PMID:40378373 | DOI:10.1371/journal.pone.0323139

PLoS One. 2025 May 16;20(5):e0323371. doi: 10.1371/journal.pone.0323371. eCollection 2025.

ABSTRACT

BACKGROUND: Artificial intelligence (AI) methods have established themselves in cardiovascular magnetic resonance (CMR) as automated quantification tools for ventricular volumes, function, and myocardial tissue characterization. Quality assurance approaches focus on measuring and controlling AI-expert differences but there is a need for tools that better communicate reliability and agreement. This study introduces the Verity plot, a novel statistical visualization that communicates the reliability of quantitative parameters (QP) with clear agreement criteria and descriptive statistics.

METHODS: Tolerance ranges for the acceptability of the bias and variance of AI-expert differences were derived from intra- and interreader evaluations. AI-expert agreement was defined by bias confidence and variance tolerance intervals being within bias and variance tolerance ranges. A reliability plot was designed to communicate this statistical test for agreement. Verity plots merge reliability plots with density and a scatter plot to illustrate AI-expert differences. Their utility was compared against Correlation, Box and Bland-Altman plots.

RESULTS: Bias and variance tolerance ranges were established for volume, function, and myocardial tissue characterization QPs. Verity plots provided insights into statstistcal properties, outlier detection, and parametric test assumptions, outperforming Correlation, Box and Bland-Altman plots. Additionally, they offered a framework for determining the acceptability of AI-expert bias and variance.

CONCLUSION: Verity plots offer markers for bias, variance, trends and outliers, in addition to deciding AI quantification acceptability. The plots were successfully applied to various AI methods in CMR and decisively communicated AI-expert agreement.

PMID:40378365 | DOI:10.1371/journal.pone.0323371

PLoS One. 2025 May 16;20(5):e0321785. doi: 10.1371/journal.pone.0321785. eCollection 2025.

ABSTRACT

BACKGROUND: In 2017, reports of adverse drug reactions worldwide reached an estimated 35 million.Chemotherapeutic agents were one of the most often implicated pharmacological classes in inducing adverse drug reactions. Adverse drug reactions increase the overall expense and mortality. Adverse drug reactions increase morbidity, mortality, hospitalization rate and financial expenses. Therefore, this study intended to assess chemotherapy-related adverse drug reactions and associated factors among adult cancer patients.

PATIENTS AND METHOD: A facility-based prospective observational study was conducted from July 2022 to October 2022 at Jimma Medical Center’s oncology unit. A standard data collection tool (Naranjo’s algorithm, modified Hartwig’s severity scale, and modified Schumock-Thornton criteria) was used for assessment of causality, severity, and preventability of adverse reactions, respectively. Socio-demographic profile and any adverse drug reactions reported were collected separately. The data was collected by one pharmacist and two nurses after giving training. Data was entered into Epidata version 4.6.0 and analyzed by SPSS version 25. Bivariate and multivariable logistic regression was conducted to identify independent predictors of the pattern of adverse drug reaction occurrence. A P-value of 0.05 was taken as statistically significant.

RESULT: Out of 154 patients enrolled in the study, 66.2% were female. The mean age of patients was 41.20 ± 13.54 years. From the total, 98 (63.6%) cases developed a total of 198 adverse drug reactions. Out of them, 59.2% were female. The most commonly encountered adverse drug reactions were nausea and vomiting (33.8%) and hair loss (29.3%). Most of the reactions were probable (61.1%) in causality, mild (66.2%) in severity, and not preventable (43.9%) in nature. Female sex (AOR = 1.054; 95% CI= (1.021-1.087); P = 0.001), number of chemotherapy treatments (AOR = 3.33; 95% CI= (1.301-8.52); P = 0.012), and elderly age (AOR = 3.065; 95% CI= (1.01-9.296); P = 0.048) were associated with occurrences of adverse drug reactions.

CONCLUSION: We can deduce from the data that adverse drug reactions are a significant concern for patients undergoing chemotherapy, with nearly two-thirds experiencing ADRs. The most common reactions are nausea and vomiting, which are mostly mild and probable. Age, gender, and the use of several chemotherapy drugs were associated with an increased risk of adverse drug reactions. Hence all concerned bodies should make an effort for early detection and take preventive measure of chemotherapy-related adverse drug reactions. Where feasible, use chemotherapy protocols with alower risk of ADRs. Evaluate dose adjustments for elderly patients. Implement protocols for risk assessment before initiating chemotherapy.

PMID:40378362 | DOI:10.1371/journal.pone.0321785