Tag: pubmed

JMIR Mhealth Uhealth. 2025 Jun 25;13:e59926. doi: 10.2196/59926.

ABSTRACT

BACKGROUND: With a focus on postoperative dysfunctions that may occur after maxillofacial tumor resection and the difficulties faced during home rehabilitation, we developed a mobile health app based on nurse-patient cooperation. The app extends rehabilitation care from hospital to home with the help of artificial intelligence, Internet of Things, and other technologies, thus helping patients to better carry out their home functional rehabilitation and meet their health needs.

OBJECTIVE: The primary objective of this quasi-experimental study is to evaluate the impact of the Intelligent Home Rehabilitation Care Platform on the quality of life, self-management, and functional impairment in patients with oral and maxillofacial head and neck tumors. We aim to determine whether the intervention through this platform can lead to significant improvements in these areas compared with traditional postdischarge care methods.

METHODS: In this study, patients with oral and maxillofacial head and neck tumors who had undergone surgery were recruited from allied hospitals in the Yangtze River Delta region, divided into an experimental group (n=138) and a control group (n=123), and received either the Intelligent Home Rehabilitation Care Platform intervention or the conventional health care and guidance, respectively. The intervention lasted 3 months, and the patients’ quality of life, self-management efficacy, and improvement in dysfunction were assessed at 1 week (baseline), 1 month (T1), and 3 months (T2) postoperatively. SPSS software (IBM Corp) was used to perform the chi-square test, rank sum test, t test, repeated-measures ANOVA, and generalized estimation equation for data analysis.

RESULTS: We analyzed the effects of the quality of life and self-management using the generalized estimating equation method. The generalized estimating equation results showed that after adjusting for age, sex, pathological histology, cancer stage, and primary site, the intervention group had a significantly higher improvement in quality of life than the control group at the T2 (regression coefficient, β=-68.020, 95 % CI -116.639 to -19.412; P=.006) stage. The degree of improvement in self-management efficacy was significantly higher in the T1 (regression coefficient, β =-7.030, 95 % CI -9.540 to -4.520; P<.001) and T2 (regression coefficient, β =-13.245, 95 % CI -16.923 to -9.566; P<.001) stages than in the control group. The results of repeated-measures ANOVA and rank sum test showed that the experimental group showed improvements in shoulder function, dysphagia, and trismus after mHealth intervention; however, the differences were not significant.

CONCLUSIONS: The Intelligent Home Rehabilitation Care Platform interventions can effectively enhance patients’ self-management efficacy, improving quality of life and facilitate recovery from dysfunctions. Therefore, mHealth may be used in oncology care to provide smarter home self-care for patients.

PMID:40561502 | DOI:10.2196/59926

JMIR Cardio. 2025 Jun 25;9:e71366. doi: 10.2196/71366.

ABSTRACT

BACKGROUND: Advances in digital technology, such as health apps and telerehabilitation systems, offer promising treatment modalities in the secondary prevention of cardiovascular disease. However, the successful adoption of digital technology in clinical practice depends on a variety of factors. A comprehensive understanding of the influencing factors on digital technology usage in health care can support the complex implementation process of digital technology in clinical practice.

OBJECTIVE: The aim of this study was to identify barriers and facilitators of digital technology usage in cardiovascular disease secondary prevention from the perspective of health care professionals, and to explore whether certain characteristics of health care professionals are related to the current usage of digital technology in clinical practice.

METHODS: We conducted an exploratory online survey, inquiring about the perspectives and uses of digital technologies in cardiovascular disease secondary prevention. We developed an original questionnaire to address the study aim. The survey invitation was distributed among health care professionals from November 2021 to February 2022, via all cardiac rehabilitation centers, all community-based disease management services for patients with chronic heart failure, and all relevant national health care professional associations in Austria. Qualitative survey data were analyzed using thematic content analysis. Quantitative survey data were analyzed using descriptive statistics, group comparison tests, and association statistics.

RESULTS: Overall, 125 health care professionals (mean age 41, SD 11 y; n=80, 64% females) across different professions and settings, including cardiac rehabilitation phases I through IV, were recruited. General readiness for using digital technologies in the care of cardiac patients was high, but only 65 (52%) respondents reported doing so. The top 3 rated barriers to digital technology use were poor user-experience of devices and apps, lack of cost coverage, and low digital competence of patients. The top 3 rated potential application areas for digital technology were organization and appointment planning, documenting treatments, and creating personalized treatment plans. The top 3 rated facilitators for digital technology use were assurance of patient safety, assurance of patients’ privacy, and availability of technical support. Greater personal use of digital technology, younger age, and higher technology affinity of health care professionals was associated with higher readiness to use digital technology with cardiac patients.

CONCLUSIONS: While there is interest in digital technology for the secondary prevention of cardiovascular disease in Austria, barriers to uptake need to be addressed. Our findings may inform the design and implementation of future digitalization projects.

PMID:40561497 | DOI:10.2196/71366

JMIR Form Res. 2025 Jun 25;9:e74043. doi: 10.2196/74043.

ABSTRACT

BACKGROUND: Despite national asthma care guidelines, care gaps persist between best-practice and clinical practice, contributing to poor health outcomes. The Provider Asthma Assessment Form (PAAF) is an electronic asthma management and Knowledge Translation tool with an embedded decision support algorithm for severe and/or uncontrolled asthma, designed to support evidence-based asthma management.

OBJECTIVE: In this study, we aimed to document baseline asthma practice patterns and determine whether the broader intervention of PAAF integration into a primary care electronic medical record (EMR) improves evidence-based asthma diagnosis and management.

METHODS: We performed a single-center pre- and postobservational study at an academic Family Health Team in Kingston, Ontario, Canada. Retrospective baseline data were collected for 2 years prior to PAAF implementation from January 2018 to December 2019. Prospective postintervention data were collected from October 2022 to July 2024. A validated adult asthma EMR case definition was applied to EMR data to identify suspected or objectively confirmed asthma cases for both datasets, on which detailed manual chart abstractions were performed. A data extraction was performed for completed PAAFs.

RESULTS: There were 230 patients in the retrospective baseline and 143 patients in the postimplementation cohort. Overall, 31.3% (n=72) of patients at baseline versus 23.8% (n=34) at postimplementation had confirmed asthma. There were significantly more pulmonary function tests requested after the implementation of the PAAF (postimplementation: n=70, 49%; baseline: n=71, 30.9%; P<.001). A significantly higher percent of postimplementation patients were on single inhaler controller and reliever therapy (postimplementation: n=31, 21.7%; baseline: n=2, 0.9%; P<.001), inhaled corticosteroid/long-acting β-2 agonist therapy (postimplementation: n=36, 25.2%; baseline: n=34, 14.8%; P=.01), and inhaled corticosteroid if their asthma was uncontrolled (postimplementation: n=69, 62.2%; baseline: n=100, 43.5%; P=.002). Barriers were significantly more commonly addressed after implementation (postimplementation: n=24, 16.8%; baseline: n=11, 4.8%; P<.001). A significantly higher average number of asthma control parameters was documented when the PAAF was used (PAAF: mean 5.4, SD 1.9; manual chart abstraction: mean 2.3, SD 1.2; P<.001). Care as assessed by key Primary Care-Asthma Performance Indicators showed improvement in the postimplementation cohort, which did not reach statistical significance.

CONCLUSIONS: The multifaceted intervention of implementing the PAAF in this primary care practice was associated with improved documentation of diagnosis status and asthma control parameters and improved adherence with evidence-based recommendations for care, such as the use of pulmonary function tests and addressing barriers to effective asthma management. However, uptake was low, and key asthma care gaps were still common. Future directions should involve evaluating the impact of the PAAF on care and outcomes after widespread implementation in primary care settings and investigating methods to increase user uptake of the PAAF.

PMID:40561494 | DOI:10.2196/74043

Ter Arkh. 2025 Jun 8;97(5):463-470. doi: 10.26442/00403660.2025.05.203250.

ABSTRACT

AIM: To systematize data on the trends of the prevalence of Helicobacter pylori infection among the Moscow adult population.

MATERIALS AND METHODS: The MEDLINE/PubMed, EMBASE, Google Scholar, and the Russian Science Citation Index were searched for studies published between January 1, 1985, and February 7, 2025, inclusive. Publications were selected based on an analysis of their titles and abstracts. Included were peer-reviewed publications in Russian and English containing data on the prevalence of H. pylori among the adult population of Moscow, studies using validated methods for the diagnosis of H. pylori based on serological, urease respiratory tests, histological and molecular methods, as well as publications containing detailed statistical processing of data suitable for inclusion in the meta-analysis.

RESULTS: The final analysis included seven studies totaling 7,581 subjects (the overall mean age of all subjects was 48.28±13.20 years). The overall prevalence of H. pylori infection in the adult population of Moscow in the analyzed pool of studies for 18 years (2006-2024) was 66.534% (95% confidence interval [CI] 42.097-86.989), including 78.661% (95% CI 59.400-92.910) when using serological diagnostic methods and 48.473% (95% CI 32.331-64.781) when using the ¹³C-urease respiratory test. Studies conducted before 2015 showed the prevalence of H. pylori infection of 81.294% (95% CI 67.202-92.109), 68.028% (95% CI 29.383-95.895) in 2015-2020, and 39.860% (95% CI 33.993-45.877) after 2020. The meta-regression analysis revealed a statistically significant decrease in the prevalence of H. pylori depending on the year of the study (regression coefficient for the year -4.22 (95% confidence interval -6.27–2.17; p<0,0099).

CONCLUSION: The meta-analysis showed a gradual regression in the prevalence of H. pylori infection in Moscow, the largest metropolis in Russia and Europe. However, infection prevalence in the adult population remains relatively high, supporting the need for continued programs of timely diagnosis of H. pylori and subsequent eradication therapy to reduce the risk of associated diseases.

PMID:40561491 | DOI:10.26442/00403660.2025.05.203250

Ter Arkh. 2025 Jun 8;97(5):434-442. doi: 10.26442/00403660.2025.05.203228.

ABSTRACT

BACKGROUND: Osteoarthritis (OA) is a common joint disease and one of the leading causes of disability worldwide. The role of vitamin D in the etiology and development of OA is still unclear, but it may be important for both diagnosis and timely therapy.

AIM: To evaluate the relationship of vitamin D levels with clinical and instrumental parameters in OA in a cross-sectional study.

MATERIALS AND METHODS: The study included 171 patients aged 40-75 with confirmed knee OA according to the American College of Rheumatology (ACR) classification, stage I-III (according to Kellgren and Lawrence). All patients signed informed consent. The mean age was 53.5±9.94 years, body mass index (BMI) was 29.8±6.4 kg/m², and disease duration was 3 [1; 7] years. For each patient, a case record form was filled out, including anthropometric indicators, medical history, clinical examination data, an assessment of knee joint pain according to the Visual Analog Scale (VAS), WOMAC, and the patient’s general health condition (PGHC). All patients underwent standard radiography, knee ultrasound examination and magnetic resonance imaging (MRI) (WORMS), densitometry of the lumbar spine and femoral neck, and laboratory tests. Statistical processing of the data was performed using the Statistica 10 software.

RESULTS: Normal vitamin D values (≥30 ng/mL) were found in 62 (36.3%) patients, low levels (<30 ng/mL) in 109 (63.7%) patients, insufficiency (<30 ng/mL and >20 ng/mL) in 66 (38.6%) patients, and deficiency (<20 ng/mL) in 43 (25.1%). Patients were divided into three groups according to the presence or absence of vitamin D insufficiency/deficiency: Group 1 included patients with normal vitamin D levels, Group 2 included patients with insufficiency, and Group 3 included patients with vitamin D deficiency. Patients of the three groups were comparable in age and disease duration but differed significantly in body weight, BMI, and waist measurement (higher in groups with reduced vitamin D values; p<0.05). Also, these patients had significantly higher VAS pain scores, total WOMAC and its components (pain, stiffness, and dysfunction), PGHC, and worse KOOS. More patients in Groups 2 and 3 had OA of the hip and hand joints, clinically detected synovitis, flat feet, and quadriceps muscle hypotrophy. Ultrasound examination significantly more often revealed a reduction of cartilage tissue on both the anteromedial and anterolateral surfaces of the knee joint; MRI showed more often osteitis in the medial condyles of the femur and tibia (p<0.05 for all values).

CONCLUSION: Our study demonstrated that low blood vitamin D levels (insufficiency/deficiency) were associated with a more severe knee OA. These patients had a large body weight, BMI, higher VAS pain values, WOMAC index (overall and its components), worse KOOS, PGHC, and smaller cartilage sizes in the medial parts of the knee joint (according to ultrasound); such patients were significantly more likely to have osteitis in the medial parts of the femur and tibia according to MRI. Also, stage II and III knee OA and OA of other localizations, clinically detected synovitis, quadriceps hypotrophy, and flat feet were more common.

PMID:40561487 | DOI:10.26442/00403660.2025.05.203228

JMIR Infodemiology. 2025 Jun 25;5:e65835. doi: 10.2196/65835.

ABSTRACT

BACKGROUND: There has been an increase in the prevalence of noncommunicable diseases in Malaysia. This can be prevented and managed through the adoption of healthy lifestyle behaviors, including not smoking, avoiding alcohol consumption, maintaining a balanced diet, and being physically active. The growing importance of using social media to deliver information on healthy behaviors has led health care professionals (HCPs) to lead these efforts. To ensure effective delivery of information on healthy lifestyle behaviors, HCPs should begin by understanding users’ current opinions about these behaviors and whether the users are receptive to recommended health practices. Nevertheless, there has been limited research conducted in Malaysia that aims to identify the sentiments and content of posts, as well as how well users’ perceptions align with recommended health practices.

OBJECTIVE: This study aims to examine social media posts related to various lifestyle behaviors, by using a combination of sentiment analysis to analyze users’ sentiments and manual content analysis to explore the content of the posts and how well users’ perceptions align with recommended health practices.

METHODS: Using keywords based on lifestyle behaviors, posts originating from X (formerly known as Twitter) and published in Malaysia between November and December 2022 were scraped for sentiment analysis. Posts with positive and negative sentiments were randomly selected for content analysis. A codebook was developed to code the selected posts according to content and alignment of users’ perceptions with recommended health practices.

RESULTS: A total of 3320 posts were selected for sentiment analysis. Significant associations were observed between sentiment class and lifestyle behaviors (χ26=67.64; P<.001), with positive sentiments higher than negative sentiments for all lifestyle behaviors. Findings from content analysis of 1328 posts revealed that most of the posts were about users’ narratives (492/1328), general statements (203/1328), and planned actions toward the conduct of their behavior (196/1328). More than half of tobacco-, diet-, and activity-related posts were aligned with recommended health practices, whereas most of the alcohol-related posts were not aligned with recommended health practices (63/112).

CONCLUSIONS: As most of the alcohol-related posts did not align with recommended health practices, the findings reflect a need for HCPs to increase their delivery of health information on alcohol consumption. It is also important to ensure the ongoing health promotion of the other 3 lifestyle behaviors on social media, while continuing to monitor the discussions made by social media users.

PMID:40561482 | DOI:10.2196/65835

JMIR Res Protoc. 2025 Jun 25;14:e68517. doi: 10.2196/68517.

ABSTRACT

BACKGROUND: Suicide in local jails occurs at a higher rate than in the general population, requiring improvements to risk screening methods. Current suicide risk screening practices in jails are insufficient: They are commonly not conducted using validated screening instruments, not collected by clinically trained professionals, and unlikely to capture honest responses due to the chaotic nature of booking areas. Therefore, new technologies could improve such practices. Several studies have indicated that machine learning (ML) models considerably improve accuracy and have positive predictive value in detecting suicide risk compared with practice as usual (PAU). This study will use administrative data and ML modeling to improve suicide risk detection at jail booking.

OBJECTIVE: This study is primarily focused on gathering preliminary information about the feasibility and practicality of using administrative data and ML modeling for suicide risk detection but also incorporates elements of hypothesis testing pertaining to clinical outcomes.

METHODS: The study uniquely contributes to our understanding of suicide risk by further validating an existing ML model developed and previously validated by the Mental Health Research Network using Medicaid outpatient health care claims data. This validation uses complete claims data on a sample of approximately 6000 individuals booked into 2 diverse jails in a midwestern state. This model validation uses 313 unique demographic and clinical characteristics from 5 years of historical health care data. It detects suicide risk in jails and postrelease by using merged jail, Medicaid, and vital records data. The study will use jail administrative data for September 1, 2021, through February 28, 2022; Medicaid records data for September 1, 2016, through March 31, 2023; and vital records data for March 1, 2022, through March 31, 2023.

RESULTS: First, the algorithm will be validated on the data gathered for the jail sample using the C-statistic and area under the receiver operating characteristic curve. Second, the resulting model will be compared with the jails’ suicide identification PAU to assess risk and detection of identified suicide attempts and deaths from intake through 120 days and 13 months after jail release. The funding timeline for this project is August 1, 2022, through July 31, 2025. The algorithm’s predictions and actual event incidence will be linked and validated in the spring of 2025, with results ready for publication in the fall of 2025.

CONCLUSIONS: The study will also investigate implementation factors, such as feasibility, acceptability, and appropriateness, to optimize jail uptake. Interview data on the implementation factors will be gathered in the summer of 2025, with expected dissemination in 2026. We hypothesize that a combination of intake screening PAU and the ML model will be the optimal approach, in that the combination will be more accurate and can have practical application in this context.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/68517.

PMID:40561472 | DOI:10.2196/68517

J Med Internet Res. 2025 Jun 25;27:e71211. doi: 10.2196/71211.

ABSTRACT

BACKGROUND: Colorectal cancer (CRC) screening rates remain disproportionately low among Hispanic and Latino populations compared to non-Hispanic White populations. While artificial intelligence (AI) shows promise in health care delivery, concerns exist that AI-based interventions may disadvantage non-English-speaking populations due to biases in development and deployment.

OBJECTIVE: This study aimed to evaluate the effectiveness of a multilingual AI care agent in engaging Spanish-speaking patients for CRC screening compared to that with English-speaking patients.

METHODS: This retrospective analysis examined an AI-powered outreach initiative at WellSpan Health in Pennsylvania and Maryland during September 2024. The study included 1878 patients (517 Spanish-speaking, 1361 English-speaking) eligible for CRC screening who lacked active web-based health profiles. A multilingual AI conversational agent conducted personalized telephone calls in the patient’s preferred language to provide education about CRC screening and facilitate fecal immunochemical test (FIT) kit requests. The primary outcome was the FIT test opt-in rate, with secondary outcomes including connect rates and call duration. Statistical analysis included descriptive statistics, bivariate comparisons, and multivariate logistic regression.

RESULTS: Spanish-speaking patients demonstrated significantly higher engagement across all measures than English-speaking patients with respect to FIT test opt-in rates (18.2% vs 7.1%, P<.001), connect rates (69.6% vs 53.0%, P<.001), and call duration (6.05 vs 4.03 minutes, P<.001). Demographically, Spanish-speaking patients were younger (mean age 57 vs 61 years, P<.001) and more likely to be female (49.1% vs 38.4%, P<.001). In multivariate analysis, Spanish language preference remained an independent predictor of FIT test opt-in (adjusted odds ratio 2.012, 95% CI 1.340-3.019; P<.001) after controlling for demographic factors and call duration.

CONCLUSIONS: AI-powered outreach achieved significantly higher engagement among Spanish-speaking patients, challenging the assumption that technological interventions inherently disadvantage non-English-speaking populations. The 2.6-fold higher FIT test opt-in rate among Spanish-speaking patients represents a notable departure from historical patterns of health care disparities. These findings suggest that language-concordant AI interactions may help address longstanding disparities in preventive care access. Study limitations include its single health care system setting, short duration, and lack of follow-up data on completed screenings. Future research should assess long-term adherence and whether higher engagement translates to improved clinical outcomes.

PMID:40561471 | DOI:10.2196/71211

Brief Bioinform. 2025 May 1;26(3):bbaf297. doi: 10.1093/bib/bbaf297.

ABSTRACT

Protein side-chain packing (PSCP), the problem of predicting side-chain conformations given a fixed backbone structure, has important implications in the modeling of structures and interactions. However, despite the groundbreaking progress in protein structure prediction pioneered by AlphaFold, the existing PSCP methods still rely on experimental inputs, and do not leverage AlphaFold-predicted backbone coordinates to enable PSCP at scale. Here, we perform a large-scale benchmarking of the predictive performance of various PSCP methods on public datasets from multiple rounds of the Critical Assessment of Structure Prediction challenges using a diverse set of evaluation metrics. Empirical results demonstrate that the PSCP methods perform well in packing the side-chains with experimental inputs, but they fail to generalize in repacking AlphaFold-generated structures. We additionally explore the effectiveness of leveraging the self-assessment confidence scores from AlphaFold by implementing a backbone confidence-aware integrative approach. While such a protocol often leads to performance improvement by attaining modest yet statistically significant accuracy gains over the AlphaFold baseline, it does not yield consistent and pronounced improvements. Our study highlights the recent advances and remaining challenges in PSCP in the post-AlphaFold era.

PMID:40561466 | DOI:10.1093/bib/bbaf297

Alcohol Alcohol. 2025 May 14;60(4):agaf034. doi: 10.1093/alcalc/agaf034.

ABSTRACT

BACKGROUND: Lithuania, a European country, has a history of high alcohol consumption per capita. To reduce harm, Lithuania has implemented the World Health Organization ‘best buys’ for alcohol control policies, notably two taxation policies in 2008 and 2017. Taxation may affect segments of the population differently; to explore this question, we investigated the effects on liver cirrhosis.

AIMS: To analyze the effect of taxation on liver cirrhosis hospitalizations and mortality across four age groups in Lithuania.

METHODS: Using a general additive mixed model, we tested taxation on monthly hospitalization and mortality rates between 2001 and 2022 (n = 264 months) across four age groups (young adults: 15-34, middle-aged adults: 35-54, older adults: 55-74, and seniors: 75+ years of age, respectively). We computed standardized hospitalizations and mortality rates (admissions and deaths per 100 000 people) based on summed counts of alcoholic liver disease and fibrosis and cirrhosis of the liver according to the International Classification of Diseases 10th Revision.

FINDINGS: Taxation was associated with the largest downward trend in liver cirrhosis mortality among middle-aged and older adults, equivalent to two fewer deaths per 100 000 individuals. In older adults and seniors, taxation was associated with downward trends in hospitalizations, but effects were less robust.

CONCLUSION: Taxation may lead to decreases in liver cirrhosis mortality across all age groups but appears to be less consistently impactful for hospitalizations. Younger and middle-aged individuals may experience increased hospitalizations. Taxation appears to impact subsections of the population differently.

PMID:40561461 | DOI:10.1093/alcalc/agaf034