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Interactive Journal of Medical Research
A new general medical journal for the 21st century, focusing on innovation in health and medical research.
Background: Next generation sequencing (NGS) has detected numerous circular RNAs (cirRNAs) in the past two decades. For example, a recent analysis of many full-length RNA-sequencing datasets identifies 139,643 human and 214,747 mouse circRNAs. Why before the NGS era few ciRNAs had been identified using Sanger sequencing thus becomes a question. Moreover, few, if any, of the numerous cirRNAs found in human cells have been shown for the procedural and mechanistic details of their formations. Objective: This essay aims to analyze whether human cells really express numerous cirRNAs and, if yes, what are the procedures and mechanisms of their formations. Methods: We rummaged through the whole Pubmed for procedural and mechanistic details of how cirRNAs were produced in human cells. We also reviewed the history of the first cirRNAs found in human and mouse cells and analyzed the genomic organizations of the genes that expressed these cirRNAs. In addition, we summarized the difficulties and pitfalls of the techniques used to identify and verify cirRNAs described in the literature. Results: CirRNAs are thought to be derived from transsplicing or poorly-defined backsplicing, recursive splicing (RS) or intron-lariat splicing (ILS). However, procedural and mechanistic niceties of how they are formed in human cells have never been shown for any single cirRNA. For example, it remains unknown whether a spliceosome is involved and, if yes, which small nuclear RNAs recruit which nucleoproteins to form the spliceosome that executes the formation of a particular cirRNA. Most reported human cirRNAs were previously missed by Sanger sequencing, which in our opinion has three possibilities that need to be tested: 1. Most of human cirRNAs are technical artifacts, which may be related to the reversely complementary regions of the pre-RNAs that form a hybrid, such as the stem of a hairpin structure. 2. Some cirRNAs may be intermediate products of a spliceosome-mediated RS or ILS with unknown details. 3. Some others may be attributed to the ribozyme of the pre-RNAs that self-ligates their two ends, which may actually be the mechanism of the so-called backsplicing that may also be related to the reversely complementary regions of the pre-RNAs. Conclusions: Until procedural and mechanistic niceties of how cirRNAs are formed have been articulated for some human cirRNAs as examples, such as whether small nuclear RNAs and spliceosomes are involved, the notion that “human cells express numerous cirRNAs” remains hypothetical. However, continuing researches on the effects of cirRNAs and the mechanisms underlying these effects are warranted, because many man-made cirRNAs may be promising medicines or tools in biomedical researches or industries.
(Toronto, ON, June 19, 2025) JMIR Publications is pleased to announce that Interactive Journal of Medical Research has received a Journal Impact Factor of 2.2, as published in Journal Citation Reports 2025 from Clarivate. This represents an increase over last year.
This achievement highlights the sustained importance of research on innovation in health and medical research, and medicine. The “interactive” part of the journal’s title focuses on the relationship between people, disciplines, organizations, systems, and/or technology.
This year’s Journal Impact Factor (2024 data) for Interactive Journal of Medical Research reflects the high-quality and impactful research contributed by the published authors, and the rigorous work of peer reviewers and the journal’s editorial board.
To view a full list of JMIR Publications journals with a Journal Impact Factor, please visit the website.
JMIR Publications recommends that authors and other parties consider alternative metrics, in combination with Journal Impact Factor, when assessing a journal’s standing and impact. While proud of its Journal Impact Factor rankings, JMIR Publications discourages misuse of citation-based impact scores.
The Interactive Journal of Medical Research (i-JMR, ISSN: 1929-073X, Journal Impact Factor of 2.2, Journal Citation Reports 2025 from Clarivate) is an interdisciplinary medical journal focusing on innovation in health, health care, and medicine. Interactive refers to the relationship between people, disciplines, organizations, systems, and/or technology (e.g. human-to-human, human-to-computer/systems, organization-to-organization, system-to-system, etc). The publications cover multiple areas of health sciences, including - but not limited to - cardiology, dermatology, dental sciences, kinesiology, neurology, nursing, nutrition, ophthalmology, and psychiatry. Innovation is evidenced through studies that: (1) present clinically relevant findings, (2) describe new medical techniques, (3) report unique medical cases, and (4) identify emerging trends in the current literature. All article types are considered for publication in i-JMR, including case reports, observational studies, interventional studies, viewpoints, bibliometric studies and literature reviews, as long as they present innovation. i-JMR is published by JMIR Publications (What is JMIR Publications?), the publisher of JMIR, the leading eHealth/mHealth journal.
i-JMR is indexed in PubMed, PubMed Central, DOAJ, Sherpa/Romeo, EBSCO, and Clarivate's Emerging Sources Citation Index (ESCI).
Background: Long COVID, or postacute COVID-19 syndrome, presents with persistent cognitive and psychological symptoms such as , anxiety, depression, and fatigue, significantly impacting quality of life and daily functioning. Digital health interventions offer a scalable, accessible solution to bridge care gaps, especially where conventional neuropsychological support is limited. However, evidence regarding their effectiveness for neuropsychiatric symptoms in long COVID remains fragmented.
Objective: This scoping review aimed to systematically identify and map the existing evidence on digital interventions targeting cognitive and psychological symptoms in individuals with long COVID. The review also sought to categorize intervention types, assess reported outcomes, and identify methodological gaps to inform future clinical and research priorities.
Methods: The review followed the Arksey and O’Malley framework and adhered to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines. Comprehensive searches were conducted in 4 databases (PubMed, Scopus, Web of Science, and ScienceDirect) from December 2024 to February 2025. Eligible studies included peer-reviewed and gray literature published in English or Spanish since 2020. Studies were screened and selected based on predefined inclusion and exclusion criteria. Data were extracted using a standardized charting form and synthesized narratively, with thematic grouping by intervention type.
Results: Of 888 records identified, 25 (2.82%) were included. Intervention types encompassed telehealth platforms, mobile health apps, virtual reality, online cognitive and psychological therapies, game-based cognitive training, neuromodulation (transcranial direct current stimulation), and multicomponent programs. Most studies reported improvements in psychological well-being, emotional regulation, and cognitive domains such as attention and memory. However, findings varied, with some interventions showing no significant cognitive gains or sustained effects. Common limitations included small sample sizes, lack of control groups, heterogeneity in outcomes and intervention protocols, and short follow-up durations. The underrepresentation of older adults and underserved populations was also noted.
Conclusions: Digital interventions show promise for addressing cognitive and psychological symptoms in long COVID, particularly when delivered as multicomponent programs. Nonetheless, the evidence base remains preliminary. Future research should prioritize high-quality randomized trials with standardized outcome measures, long-term follow-up, and diverse participant samples. Addressing barriers related to digital literacy and access will be essential to ensure equity and real-world effectiveness.
Trial Registration: OSF Registries 10.17605/OSF.IO/HX7UE; https://osf.io/hx7ue/overview
Background: Observation of COVID-19 rebound after nirmatrelvir plus ritonavir (NPR) has driven important questions surrounding one of the only direct-acting antiviral treatments for COVID-19.
Objective: The objective of this study was to examine the epidemiology of COVID-19 rebound among COVID-19–positive outpatients in the United States who independently decided whether or not to take NPR.
Methods: This prospective, decentralized observational cohort study was conducted from August 2022 through December 2023 and included frequent proctored COVID-19 rapid antigen tests and self-report symptom surveys for 15 days. The primary outcome was the incidence of viral and symptom rebound. Secondary outcomes included time to initial viral and symptom clearance, rebound probability among patients who cleared by day 15, and symptom frequency.
Results: Of 917 consenting participants, 669 (73%) were eligible for inclusion in the analysis (n=443, 66% in the NPR group; n=226, 34% in the control group). The mean age was 46.1 (SD 12.9) years, 62.6% (n=419) of participants were female, and 49.2% (n=329) had at least one preexisting condition. Overall, 15-day cumulative incidence was higher in the NPR group than the control group for both viral (70/443, 15.8% vs 12/226, 5.3%) and symptom (73/443, 16.5% vs 19/226, 8.4%) rebound. Time to initial viral and symptom clearance was similar between groups, and among those who experienced clearance by day 15, the probability of viral rebound (NPR: 19.1%, 95% CI 15.1%-24.0% vs control: 7%, 95% CI 4.0%-12.6%; <.001) and symptom rebound (NPR: 47.7%, 95% CI 36.1%-60.8% vs control: 16.9%, 95% CI 10.9%-25.7%; <.001) was higher in the NPR group than the control group.
Conclusions: This study demonstrates that while COVID-19 rebound occurs in both NPR-treated and untreated outpatients, the incidence is higher in the NPR group.
Background: The use of artificial intelligence (AI) in medical imaging has been growing exponentially. Understanding patient perceptions and factors influencing their views of AI is critical to develop adequate strategies to support implementation and acceptance.
Objective: This study aims to investigate the constructs that influence patients’ perceptions and acceptance of AI’s use in the analysis of their medical images to support screening and diagnosis.
Methods: A systematic review was conducted to meet the research objective. Relevant articles were found by searching 5 databases. Data were extracted using an iteratively refined framework and synthesized narratively due to heterogeneity in study designs, populations, health care contexts, and outcomes.
Results: A total of 59 relevant studies were included in the review. Patient acceptance of AI in medical image analysis emerged from multiple interacting factors. The most consistently reported determinant in 48 studies was that AI implementation should prioritize human-in-the-loop models, positioning AI as supportive tools, working in conjunction with health care providers rather than as an autonomous decision-maker. Other factors identified were performance of the AI, clarity of accountability, trust, and ethical factors. Patients’ individual characteristics such as demographics and health history were also noted to influence acceptance indirectly. The review findings were used to draft a conceptual model to draw attention to the complex relationship among the identified factors.
Conclusions: This review informed the development of a conceptual model illustrating the complex and interactive factors shaping patient acceptance of AI in medical imaging, which can be tested prospectively in future studies. Our results highlight that patients’ likelihood of accepting AI cannot be attributed to a few factors. Instead, promoting acceptance will require a holistic approach where multiple factors are considered simultaneously and adapted for each use case.
Background: During a public health emergency, emergency department (ED) clinicians can improve care delivery if they identify and adopt innovations that are safe and effective. However, little is known about the factors that impact ED clinicians’ decision-making around using or discontinuing innovations when evidence-based information is limited.
Objective: The goal of this study was to understand the processes and factors that led ED clinicians to discontinue (deimplement) the use of COVID-19 care innovations.
Methods: This is a qualitative study using semistructured focus groups with ED clinicians from 8 hospitals across the United States. Hospitals were purposively sampled and recruited to capture a diversity of perspectives based on location, facility type (academic or community hospital), rurality (urban or rural), and safety-net status. In this study, 17 physicians, 7 advanced practice providers, 18 nurses, and 7 respiratory therapists participated. We utilized both inductive and deductive techniques to perform content and thematic analysis of transcripts.
Results: Clinicians shared that their own experiences (eg, direct observation of patient outcomes), contextual factors, and emerging research evidence contributed heavily to decisions about deimplementing innovations during the COVID-19 pandemic. Processes related to discontinuing innovations depended on leadership guidance and collaboration among colleagues. However, in some cases, there were no official processes to discontinue innovations, and innovations were passively deimplemented.
Conclusions: Decision-making regarding the discontinuation of innovation in ED settings during the COVID-19 pandemic differed from routine conditions due to the lack of information and the rapid evolution of evidence within a short period of time. The level of evidence required to implement and deimplement innovations was significantly lower. Our findings indicate that factors influencing deimplementation during a public health emergency were highly localized and were treated similarly to pilot tests of new innovations. Future work is necessary to develop mechanisms for implementing promising innovations during evolving public health emergencies and monitoring their effectiveness and safety after implementation, enabling evidence-based decisions about whether to continue implementation or proceed with deimplementation.
Background: Children’s eating habits are formed at an early age, making childhood a crucial period for introducing novel foods, such as pulse-based food products. Pulse Discovery Toolkit (PDTK) intervention was designed to increase familiarity with pulses and to eventually contribute to the consumption of pulse-based foods among preschool children in childcare centers (CCs).
Objective: To determine PDTK’s impact on knowledge, acceptability, and consumption of pulse-based foods among preschool children attending CCs, and to assess its feasibility and acceptability by early childhood educators (ECE) and cooks. The nutrient contents and food group servings of pulse-based intervention recipes in the PDTK were also compared with regular CC recipes.
Method: The PDTK intervention was delivered over a 3-month period in 2 CCs in Saskatoon (50 children, 8 staff). The intervention, which integrated taste exposure and nutrition education, consisted of 12 child-friendly weekly lessons, a food service guide for cooks, 15 recipes for pulse-based foods, 4 intervention recipes incorporated in the CC menu, and 4 parent newsletters. Mixed methods were used with pre- and postintervention knowledge tests, plate waste measurement, sensory evaluation, ECE and cook’s perspective, and nutrient content comparison of the intervention and control foods from the regular childcare menu to evaluate the intervention’s impact.
Result: Improvements in correct identification of chickpeas (2/21 [10%] at preintervention to 7/21 [33%] at postintervention, =.074), beans (8/21 [38%] to 11/21 [52%], =.68), and peas (6/21 [27%] to 8/21 [38%], =.61) were not statistically significant. Children consumed higher amounts of the regular recipes (293.54, SD 27.65; 178.46, SD 24.33) than the intervention recipes (211.56, SD 25.61; 108.83, SD 21.97) at both times, respectively. However, at the end of the intervention, significant differences were only observed in the amount of total food consumption (=.049) and the protein content (=.04) when consumption proportion was examined, with both being higher for the control recipes in comparison to the intervention recipes. The majority (92% and 72%) of the children rated the refried bean wrap and lentil smoothie, “yummy,” respectively. Most of the intervention recipes have lower energy, fat, and sodium content compared with the regular CC recipes. Findings from ECE semistructured interviews and the lesson plan evaluations revealed that the ECEs reacted favorably to the curriculum. The cooks from the participating CCs did not report any barriers to cooking pulses in their facility. However, the need for modification to make the recipes easier to cook in CCs was noted in our study.
Conclusions: With a few modifications to make some of the lessons more age-appropriate and some of the recipes easier to cook, it is feasible to implement the PDTK in CCs in order to promote regular consumption of pulses.
International Registered Report Identifier (IRRID): RR2-10.2196/22775
Background: Major depressive disorder (MDD) and treatment-resistant depression (TRD) are heterogeneous conditions in which key clinical details are split across structured fields and free-text notes in electronic health records (EHRs), constraining population-level insight and timely audit of care quality.
Objective: This study aims to present a clinician-oriented, artificial intelligence-supported real-world evidence (RWE) methodology integrating structured and unstructured EHR data to profile MDD and TRD, and report comorbidity patterns from a 2-site pilot. This analysis reports the first objective of the MOOD project, which is to characterize the real‑world clinical and disease severity profile of patients with MDD and treatment‑resistant depression, providing a necessary foundation for subsequent evaluations of treatment patterns and outcomes.
Methods: We conducted a retrospective study in 2 Belgian hospitals (September 2021-June 2023). Adults (aged ≥18 years) with MDD were identified via DSM-IV (Diagnostic and Statistical Manual of Mental Disorders [Fourth Edition]) and ICD-10 (International Statistical Classification of Diseases, Tenth Revision) codes or natural language processing-detected note mentions; bipolar depression was excluded. TRD was defined as initiation of a third distinct antidepressant, supplemented by explicit mentions of TRD in notes. Structured data (demographics, diagnoses, medications, and hospitalizations) were harmonized in an Observational Medical Outcomes Partnership warehouse. Free-text notes were processed with a natural language processing pipeline to capture symptoms, psychiatric comorbidities, and contextual events.
Results: We identified 1147 adults with MDD, of which 46% (524/1147) met TRD criteria. Females comprised 62.9% (722/1147) and mean (SD) age was 57.8 (18.4) years. Mortality was 13.3% (152/1147) overall (57/1147, 10.9% TRD vs 95/1147, 15.2% non-TRD). Common medical comorbidities were central nervous system diseases (477/1147, 41.6%) and heart diseases (349/1147, 30.4%). Dementia was more frequent in TRD (42/1147, 8% vs 32/1147, 5.1%), whereas obesity was higher in non-TRD (70/1147, 11.2% vs 46/1147, 8.8%). Anxiety disorder occurred in 35.4% (406/1147) overall and was more prevalent in TRD (229/1147, 43.7% vs 177/1147, 28.4%); personality and panic disorders also trended higher. Severity was sparsely documented (severe MDD 170/1147, 14.8%) and standardized scales were rarely recorded.
Conclusions: We present a step-by-step artificial intelligence-supported methodology tailored for clinicians, discussing challenges in integrating RWE into psychiatry, and identifying opportunities to enhance data collection with minimal workflow changes, which emphasizes the transformative potential of RWE systems in mental health research.
Trial Registration:
Background: Objective indicators are urgently needed to evaluate and monitor disease progression in patients with psoriasis.
Objective: This study aimed to verify the correlations between blood count–derived inflammatory markers and the Psoriasis Area and Severity Index (PASI) among patients with psoriasis and explore the value of applying the PASI in combination with proinflammatory factors.
Methods: This was a cross-sectional observational study that enrolled 719 patients from 2 tertiary hospitals. Receiver operating characteristic curve analysis and binary logistic regression models were applied to assess the evaluative power of blood count–derived inflammatory markers and their consistency with the PASI for stratifying psoriasis severity. The association with the PASI and the combination with proinflammatory factors of the blood count–derived inflammatory markers in 60 patients were analyzed. The exploratory association between blood count–derived markers and proinflammatory factors was analyzed using product terms. To ensure robustness, multivariable combined models were evaluated using receiver operating characteristic curves and decision curve analysis. Model performance was further validated via calibration plots and a predictive nomogram, with the decision curve analysis net benefit axis increased to 1.0 for comprehensive visualization.
Results: The area under the curve showed that the systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), and aggregate index of systemic inflammation (AISI) were effective in reflecting psoriasis severity and showed advantages in patients with psoriasis complicated by arthritis and cardiovascular metabolic diseases. The comprehensive test showed quite appropriate consistency of the SIRI and PASI in distinguishing severity. The SII, SIRI, and AISI were significantly correlated with interleukin (IL)-6 in lesions (all <.05), and the combinations of these indices with IL-6, IL-1, and IL-17 were also significantly correlated with the PASI (all <.05).
Conclusions: Blood count–derived inflammatory markers could better reflect the inflammation of patients with psoriasis. The SII, SIRI, and AISI have important clinical significance in evaluating disease severity. The combination with proinflammatory factors showed an advantage.
Background: Emergency department (ED) overcrowding is a persistent global health issue associated with adverse patient outcomes, diminished staff performance, and compromised health-system efficiency. Despite widespread recognition of the problem, there is no universally accepted approach to monitoring ED overcrowding. The use of disparate, nonstandardized indicators hampers cross-country comparison and the development of effective policies. A comprehensive synthesis of indicators currently used is essential to guide the adoption of robust, evidence-based metrics across diverse health care settings.
Objective: This study aims to identify, consolidate, and categorize indicators that have been used internationally to assess ED overcrowding and to highlight gaps in their use.
Methods: A comprehensive scoping review was conducted from October to November 2023 using four databases: PubMed, Scopus, Emerald Insight, and Google Scholar. Studies were systematically searched using predefined eligibility criteria. Level 1 and 2 screening were independently conducted by 9 researchers (NNMN, KASIP, NFS, NJN, MK, ZL, NNRA, LKY, and ISS) to minimize bias and enhance reliability, and discrepancies were resolved by consensus. A third reviewer (ISS) performed a full-text review, synthesis, and descriptive analysis. Indicators were categorized into input, throughput, and output. Input refers to factors driving ED demand, throughput encompasses internal ED processes such as triage, diagnostics, and treatment, and output addresses challenges in transferring patients to inpatient beds, such as bed shortages or delays. Descriptive analyses were then used to consolidate these indicators and to establish their relative importance. They were ranked based on frequency of reporting across diverse countries and health care settings.
Results: Out of 1347 articles screened, 117 articles were included in the study. A total of 307 indicators were retrieved and then consolidated into 26 distinct indicators. The majority of indicators were classified within the throughput domain (209/307, 68%), followed by the output domain (62/307, 20%) and the input domain (36/307, 12%). The most common throughput indicator, which was frequently reported, was ED length of stay, cited 87 times, followed by left without being seen and waiting time, each reported 30 times. Length of stay consistently emerged as a primary marker of systemic bottlenecks and operational inefficiencies across health care systems.
Conclusions: This review indicates that throughput measures, particularly length of stay, dominate current approaches to assessing ED overcrowding, whereas input and output indicators remain comparatively underrepresented. By consolidating 26 distinct indicators from 117 studies, this study provides a comprehensive evidence base to support the standardization of metrics for monitoring ED overcrowding internationally. These findings offer practical guidance for policymakers and health care leaders seeking to refine performance indicators, enhance benchmarking, and evaluate interventions aimed at improving patient flow. Further research should prioritize validation of underused indicators and the development of composite measures that better capture the complexity of ED crowding across diverse health care settings.
Background: The use of augmented reality (AR) and virtual reality (VR) to address addictive behaviors such as substance use disorders and gambling disorders has been growing. However, little has been done to explore the use of AR and VR in the treatment of other behavioral addictions.
Objective: This scoping review aims to provide an overview of existing literature on AR and VR interventions for behavioral addictions. Specifically, the research questions are as follows: (1) What behavioral addictions or behavioral harms are being treated using AR and/or VR? (2) What AR and/or VR treatment interventions are being used to treat these behavioral addictions?
Methods: This scoping review was conducted based on the framework first proposed by Arksey and O’Malley, later refined by Levac et al, and further outlined in the Joanna Briggs Institute (JBI) Manual for Evidence. The literature was searched in the following databases: CINAHL, PsycArticles, PsycInfo, PubMed, and Web of Science, with Google advanced search complementing the search on Feb 22, 2023. Studies were screened by 2 independent reviewers based on inclusion criteria (all ages; any behavioral addiction, problematic behavior, or behavioral harm; AR or VR treatments and interventions) and exclusion criteria (pornography, sexual, and paraphilic disorders). Discrepancies were resolved by third and fourth reviewers. As this study is a scoping review, risk of bias was not assessed. Data were extracted and presented in tabular form as well as through conceptual analysis as a narrative summary.
Results: A total of 9 studies were included in this review, 4 studies on video gaming and 5 studies on gambling behaviors. Participants’ age ranged from 12 to 65 years. Only the use of VR was identified. VR was used as a platform for cue exposure therapy and skills training in both gaming and gambling disorders. VR therapy was effective alone or in combination with other treatments and was comparable to traditional interventions. No adverse effect was reported in the studies.
Conclusions: VR is efficacious in treating behavioral addictions and can replace or be used in conjunction with traditional methods. Future directions include using VR with other psychotherapy or relapse prevention, applying VR to treat other addictions, and investigating harmful side effects of VR use. The frequency and duration of sessions can also be optimized. A limitation of this study is that there may be other documents beyond those published and searched in gray literature that could not be included in this review due to time and resource restrictions. The use of AR in the treatment of behavioral addictions did not yield any results in this review. However, VR application in behavioral addiction is promising, potentially efficacious, and capable of multiple applications.
Trial Registration:
Background: Recommender systems are pivotal in organizing information to enhance noticeability, reduce overload, and streamline decision-making. They can be even more effective if combined with digital nudges. Digital nudging is a subtle approach that combines design, information, and interaction elements to create a choice architecture that can guide user behavior in digital environments. While promising in many fields, there is a notable gap in health promotion, particularly because digital nudges and recommender systems can encourage and support sustained healthier choices in nutrition, physical activity (PA), and sedentary behavior reduction to prevent overweight and obesity.
Objective: This scoping review addresses these gaps by exploring how digital nudges and recommender systems are used in obesity prevention.
Methods: We prospectively published the scoping review protocol and adhered to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. Eligibility was defined using the PCC (Population, Concept, Context) framework. We searched 7 bibliographic databases (MEDLINE and PsycINFO via Ovid, Web of Science, CINAHL via EBSCO, Scopus, ACM Digital Library, and IEEE Xplore) up to October 2023. Following a 2-stage screening by independent reviewers, we selected 68 articles that included 94 user evaluations.
Results: Most articles (36/68, 53%) report on recommender systems focused on nutrition, with fewer (16/68, 23%) aiming to promote PA. Most studies on digital nudges (11/68, 16%) targeted nutrition-related nudges for shopping and meal selection (8/68, 2%). Articles address PA and sedentary behavior less frequently (3/68, 4%). Three out of 68 (4%) articles report on recommender systems in combination with games, and 2 out of 68 (3%) articles report on recommender systems and digital nudges. Approaches to item retrieval vary widely, with 31 out of 68 (46%) articles failing to describe their methods. In the scoping review, we found a discrepancy between the target group for which the system was developed and the group with which the evaluation was conducted. Sixty-eight evaluations report positive results, while 26 studies report mixed, negative, or no-difference results.
Conclusions: Integrating digital nudges and recommender systems might hold potential in overweight and obesity prevention by subtly encouraging healthier lifestyle choices. However, the heterogeneity in study designs, outcome measures, and reporting quality limits the comparability of findings and makes it difficult to draw robust conclusions about effectiveness. Future work should include detailed definitions, mechanism descriptions, broader geographic representation, and rigorous intervention testing and user evaluations to fully leverage these systems for improved health outcomes and to support sustainability and well-being objectives.
International Registered Report Identifier (IRRID): RR2-10.1136/bmjopen-2023-080644
Background: Occupational e-mental health (OeMH) interventions emerged as a promising solution to prevent common mental health problems and enhance well-being and work performance. However, they must be subject to robust and reliable assessments for effectiveness.
Methods: A multimodal e-mental health intervention (EMPOWER [The European Platform to Promote Wellbeing and Health in the Workplace]) delivered over 7 weeks was developed and evaluated through a cluster randomized controlled trial conducted mainly in small to medium enterprises and public agencies from Spain (n=127), Finland (n=141), Poland (n=51), and the United Kingdom (n=389) between February 2022 and May 2024 (recruitment finalized in September 2023 and follow-up completed in May 2024). Inclusion criteria were being 18+ years, having a smartphone, sufficient language knowledge, and agreeing to participate. Clusters (companies or departments) were randomized to intervention or control conditions. The primary outcome was presenteeism, and secondary outcomes were depression and anxiety symptoms, etc, all measured at baseline, postintervention, and in 21 weeks after program completion. The analysis was performed as an intention-to-treat approach using adjusted linear mixed models and as per protocol analysis comparing outcomes by level of engagement.
Results: A total of 347 participants were allocated to the intervention group and 361 to the control group. In the overall sample, the intention-to-treat analysis detected no statistically significant short-term (7 wk) or long-term (21 wk postintervention) effects of the EMPOWER intervention on presenteeism (postintervention =2.186; 95% CI −2.424 to 6.796, follow-up =1.294; 95% CI −3.608 to 6.396) and on other secondary outcomes such as depressive symptoms (postintervention =−0.052, 95% CI −1.02 to 0.905, follow-up =0.202, 95% CI −0.840 to 1.245), anxiety symptoms (postintervention =−0.328, 95% CI −1.168 to 0.512, follow-up =0.375, 95% CI −0.537 to 1.287), or general stress level (postintervention =0.385, 95% CI −0.195 to 0.965, follow-up =0.123, 95% CI −0.502 to 0.749). Subgroup analyses yielded several notable results, with significant differences between age groups, gender, and psychological symptoms at baseline. The per-protocol analysis showed no significant differences between participants who actively engaged with the intervention (119/347, 34%) and those who did not. Implementation challenges were related to technical problems, the complexity of this study’s design, external factors, co-design strategy, and organizational barriers, which led to a smaller sample size, high attrition rates, and low adherence.
Conclusions: Our study provides evidence from a large cluster randomized controlled trial evaluating an OeMH intervention implemented in workplace settings, including small to medium enterprises and public agencies in Europe. Although no overall effectiveness was observed, this study contributes important methodological and implementation insights, highlighting the challenges of evaluating OeMH interventions. These findings suggest that future interventions should prioritize feasibility testing, organizational readiness, user engagement, and more targeted and pragmatic evaluation approaches to enhance real-world impact.
Trial Registration: ClinicalTrial.gov NCT04907604; https://clinicaltrials.gov/study/NCT04907604
International Registered Report Identifier (IRRID): RR2-10.1177/20552076221131145
Background: The association between depressive symptoms and cardiovascular diseases is well established. However, their impact on the incidence of stroke in individuals with cardiovascular-kidney-metabolic (CKM) syndrome remains unclear.
Objective: This study aims to investigate the impact of depressive symptoms at different stages of CKM syndrome on the incidence of new-onset stroke.
Methods: This study used data from the China Health and Retirement Longitudinal Study. Depressive symptoms at baseline were assessed using the Center for Epidemiologic Studies Depression Scale, with stroke incidence determined through standardized follow-up questionnaires. Cox regression and restricted cubic spline regression were used to evaluate the association between depressive symptoms and stroke risk.
Results: The analysis included 9593 participants (n=5180, 54.92% male; mean age of 60.89, SD 9.39 y), classified into CKM stages 0 to 3. Fully adjusted Cox regression showed that each 1-point increase in depressive score was associated with a 3% higher stroke risk (hazard ratio 1.03, 95% CI 1.02‐1.04; <.001). Restricted cubic spline regression confirmed a significant positive linear relationship between depressive symptoms and stroke incidence (<.001).
Conclusions: This cohort study demonstrates a positive linear association between depressive symptoms and increased stroke incidence in individuals with CKM syndrome (stages 0‐3). These findings highlight the importance of emotional health management, suggesting that effective depression treatment may help reduce stroke risk through inflammation reduction and lifestyle improvements.
Background: Next generation sequencing (NGS) has detected numerous circular RNAs (cirRNAs) in the past two decades. For example, a recent analysis of many full-length RNA-sequencing datasets identifie...
Background: Next generation sequencing (NGS) has detected numerous circular RNAs (cirRNAs) in the past two decades. For example, a recent analysis of many full-length RNA-sequencing datasets identifies 139,643 human and 214,747 mouse circRNAs. Why before the NGS era few ciRNAs had been identified using Sanger sequencing thus becomes a question. Moreover, few, if any, of the numerous cirRNAs found in human cells have been shown for the procedural and mechanistic details of their formations. Objective: This essay aims to analyze whether human cells really express numerous cirRNAs and, if yes, what are the procedures and mechanisms of their formations. Methods: We rummaged through the whole Pubmed for procedural and mechanistic details of how cirRNAs were produced in human cells. We also reviewed the history of the first cirRNAs found in human and mouse cells and analyzed the genomic organizations of the genes that expressed these cirRNAs. In addition, we summarized the difficulties and pitfalls of the techniques used to identify and verify cirRNAs described in the literature. Results: CirRNAs are thought to be derived from transsplicing or poorly-defined backsplicing, recursive splicing (RS) or intron-lariat splicing (ILS). However, procedural and mechanistic niceties of how they are formed in human cells have never been shown for any single cirRNA. For example, it remains unknown whether a spliceosome is involved and, if yes, which small nuclear RNAs recruit which nucleoproteins to form the spliceosome that executes the formation of a particular cirRNA. Most reported human cirRNAs were previously missed by Sanger sequencing, which in our opinion has three possibilities that need to be tested: 1. Most of human cirRNAs are technical artifacts, which may be related to the reversely complementary regions of the pre-RNAs that form a hybrid, such as the stem of a hairpin structure. 2. Some cirRNAs may be intermediate products of a spliceosome-mediated RS or ILS with unknown details. 3. Some others may be attributed to the ribozyme of the pre-RNAs that self-ligates their two ends, which may actually be the mechanism of the so-called backsplicing that may also be related to the reversely complementary regions of the pre-RNAs. Conclusions: Until procedural and mechanistic niceties of how cirRNAs are formed have been articulated for some human cirRNAs as examples, such as whether small nuclear RNAs and spliceosomes are involved, the notion that “human cells express numerous cirRNAs” remains hypothetical. However, continuing researches on the effects of cirRNAs and the mechanisms underlying these effects are warranted, because many man-made cirRNAs may be promising medicines or tools in biomedical researches or industries.
Background: Burnout is highly prevalent among undergraduate medical students and is associated with adverse outcomes including depression, anxiety, psychological distress, and suicidal ideation. Spiri...
Background: Burnout is highly prevalent among undergraduate medical students and is associated with adverse outcomes including depression, anxiety, psychological distress, and suicidal ideation. Spirituality and religiosity are increasingly recognized as potential coping resources that may limit burnout and improve well-being among medical students. However, existing studies vary substantially in how spirituality and burnout are defined and measured. Objective: The goal of this scoping review was to synthesize evidence on the relationship between spirituality and burnout-related outcomes, including psychological distress and well-being, among undergraduate medical students. Methods: A scoping review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). PubMed, Scopus, Web of Science, and PsycINFO were searched. Two independent reviewers screened studies and extracted data, with disagreements resolved by a third reviewer. Extracted data included study characteristics, measurement instruments, and key findings related to spirituality and burnout-related outcomes. Results: Thirty-nine studies published from 2007 to 2025 across nineteen countries met inclusion criteria. Most were single site, cross sectional surveys with convenience samples. Sample sizes ranged from about 16 to 1,417. About half used validated spirituality measures (e.g., FACIT-Sp, SWBS, DUREL or Brief COPE); others used single item indicators. Burnout itself was measured less often than stress or mood symptoms. Overall, higher spirituality or intrinsic religiosity was frequently associated with lower burnout stress, anxiety, depressive symptoms, and suicidal ideation, and higher resilience, empathy, life satisfaction, and quality of life. Qualitative work found that spirituality provided meaning, comfort, belonging, and moral grounding during training. A smaller set of studies reported null or mixed findings, often when spirituality was measured with single items or in universities with low religious participation and limited formal support for spiritual practice. Conclusions: Across diverse settings, spirituality is commonly used by medical students and is frequently linked with better mental health. Measurement diversity and the dominance of cross-sectional designs limit causal inference. Future work should use clearer constructs, common validated tools, and prospective or interventional designs. These findings may help inform the development of more holistic and inclusive wellness initiatives within medical education that recognize the potential role of spirituality in supporting student mental health and resilience. Clinical Trial: This protocol is registered on the Open Science Framework: https://doi.org/10.17605/OSF.IO/TQWSK
Background: Healthcare-associated infections (HAIs) remain a significant challenge for healthcare facilities worldwide, contributing to patient morbidity, mortality, and substantial economic burden. I...
Background: Healthcare-associated infections (HAIs) remain a significant challenge for healthcare facilities worldwide, contributing to patient morbidity, mortality, and substantial economic burden. In the United States alone, the Centers for Disease Control and Prevention (CDC) estimates approximately 1 in 31 hospitalized patients acquires at least one HAI during their stay, resulting in billions of dollars in preventable healthcare costs annually [1]. Despite longstanding evidence-based guidance on infection prevention, sustained improvements in infection rates have been difficult to achieve across diverse healthcare settings.
Electronic hand hygiene monitoring (EHHM) systems offer a promising approach to enhancing adherence to infection prevention protocols while providing robust data for operational decision-making. By delivering real-time feedback to healthcare workers and tracking performance at the unit and facility level, these systems can identify and correct lapses in hand hygiene behavior, a primary contributor to HAIs [2]. Prior studies demonstrated that automated monitoring has improved compliance and reduced infection rates, though long-term, multi-facility analyses remain limited [3]. Objective: This analysis evaluates HAI performance among 25 client facilities of BioVigil Technologies, an EHHM vendor based in Ann Arbor, Michigan. This study uses publicly reported CMS data, assessing both infection outcomes and operational impact. By comparing pre- and post-implementation periods, we aim to quantify the clinical and economic benefits of EHHM across a variety of hospital types and sizes, providing insight into strategies for infection prevention improvement. Methods: Facilities were included if they met three predefined criteria: BioVigil’s EHHM implementation must have occurred in 2023 or earlier; CMS publicly reported HAI data had to be complete for both the 2024 calendar year and the year immediately preceding implementation; and CMS HAI reporting had to be available at the individual facility level. These criteria yielded a final study population of 25 healthcare facilities.
The facilities included 16 short-term acute care (STAC) hospitals, one long-term acute care (LTAC) hospital, seven critical access hospitals, and one VA hospital, collectively comprising 4,198 beds and 284 clinical units. CMS-reported HAIs for STAC hospitals included CAUTI, CLABSI, MRSA, SSI, and CDI; LTAC, critical access, and VA hospitals reported CAUTI, CLABSI, and CDI. Earliest full EHHM implementation occurred in 2016 (two facilities) and most recent in 2023 (three facilities).
This retrospective, observational analysis evaluated HAI outcomes aggregated at the hospital level. Percent change from baseline to 2024 was calculated for each facility and across the study population. Descriptive statistics, including mean, median, and 95% confidence intervals, characterized sustained changes in infection counts. EHHM operational data from 2024 were also analyzed to quantify hand hygiene opportunities, real-time corrective reminders, and overall compliance rates. All data were derived from publicly available CMS reports and de-identified operational records; no patient-level data was used. Results: In 2024, BioVigil’s EHHM system captured 67,663,570 hand hygiene opportunities across all 25 facilities. During this period, 1,112,148 potential cross-contamination events were corrected in real time through badge-based reminders. This contributed to an average hand hygiene compliance rate of 91.25% across the study population.
Of the 25 facilities, 22 demonstrated reductions in total HAI counts compared to their pre-implementation baseline. Four facilities achieved net-zero HAIs in 2024, representing a 100% reduction. One facility exhibited no change, and two experienced minimal increases of two and four cases, respectively — both from unusually low baseline years that likely underrepresent each facility’s true pre-EHHM infection burden.
Across all 25 facilities, the mean sustained HAI reduction was 46.95% (95% CI 35.5–58.4%), closely aligning with the median of 50%. Among the 22 improving facilities, the mean reduction was 56.25% (95% CI 43.2–69.3%) with a median of 55.13%, collectively representing 300 fewer CMS-reported HAI cases in 2024. Using a conservative average direct cost of $29,412 per HAI case [4], this reduction corresponds to an estimated $8.82 million in avoided costs. This estimate excludes extended length of stay, readmissions, and CMS value-based purchasing penalties, meaning the true economic benefit is likely substantially greater.
Operational efficiencies were also observed: 16 of 25 facilities reported hand hygiene data to The Leapfrog Group. Had these facilities relied exclusively on manual observation, an estimated 136,620 staff hours and approximately $5.74 million in associated labor costs would have been required in 2024 [5]. Together, these findings highlight the combined clinical and operational value of automated hand hygiene monitoring at scale. Conclusions: In conclusion, this analysis highlights that the majority of BioVigil Technologies’ clients experienced noticeable HAI reductions in 2024 compared to pre-implementation performance, regardless of system use duration. These outcomes suggest that electronic hand hygiene monitoring represents an effective, sustainable, and data-driven strategy to support infection prevention programs, improve patient safety, and enhance healthcare system efficiency. Continued adoption of scalable monitoring technologies may play an important role in advancing sustained infection prevention performance across diverse healthcare settings. Clinical Trial: Electronic hand hygiene monitoring; Infection Reduction; Clinical outcomes
Background: Clinical skills training is central to medical education, yet traditional teaching methods face persistent challenges including inconsistent patient exposure, subjective feedback, and limi...
Background: Clinical skills training is central to medical education, yet traditional teaching methods face persistent challenges including inconsistent patient exposure, subjective feedback, and limited faculty and resource availability. Artificial intelligence (AI), encompassing machine learning, deep learning, and expert systems, offers emerging opportunities to address these gaps through adaptive, data-driven educational tools. Despite rapid AI adoption in clinical practice, structured integration into medical curricula remains limited. Objective: This structured narrative review synthesizes current evidence on the role of AI in clinical skills training across undergraduate and postgraduate medical education, with a focus on efficacy across skill domains, curricular integration requirements, and ethical considerations for responsible implementation. Methods: A structured literature search was conducted across PubMed, Scopus, and Google Scholar for studies published between January 2019 and June 2025. A total of 42 studies were included in the final synthesis: 27 empirical investigations encompassing randomized controlled trials, systematic reviews, scoping reviews, observational studies, and surveys, and 15 non-empirical sources including policy frameworks, governance perspectives, and protocols. Findings were synthesized thematically. Results: Evidence across three converging domains was identified. First, AI demonstrates meaningful efficacy signals in procedural and surgical skills training, with one randomized controlled trial demonstrating AI tutoring to be non-inferior to expert instruction, while diagnostic reasoning and non-technical skills show early but more exploratory evidence. Second, a persistent disconnect exists between AI adoption in clinical practice and curricular scaffolding, with over 75% of surveyed students reporting no formal AI training despite high motivation among both students and faculty. Third, algorithmic bias, data privacy, deskilling through over-reliance, and infrastructure disparities represent structural equity and ethics concerns requiring deliberate governance frameworks. Conclusions: AI holds meaningful potential for clinical skills training, but it requires system-level investment in pedagogically grounded curricular integration, standardized competency frameworks, and equity-centered ethical governance. Future research should prioritize multi-institutional, longitudinal studies that link AI-enhanced educational outcomes to real-world clinical performance.
Background: Chronic kidney disease (CKD) affects more than 850 million people worldwide, yet the emotional and psychosocial burdens remain underrecognized in nephrology practice. This review explores ...
Background: Chronic kidney disease (CKD) affects more than 850 million people worldwide, yet the emotional and psychosocial burdens remain underrecognized in nephrology practice. This review explores the overlooked dimensions of loneliness, uncertainty, and emotional suffering in CKD, drawing attention to their implications for both patients and caregivers. Objective: The objective of the current review article is to elucidate the mechanisms of the distresses experienced by the hemodialysis patients and their carers Methods: We conducted a narrative synthesis of qualitative and quantitative studies across pediatric, adult, and elderly populations, with additional perspectives from culturally and linguistically diverse groups and caregivers Results: Loneliness and social isolation affect more than 40% of dialysis patients and are consistently linked with depression, reduced adherence, hospitalization, and increased mortality. Uncertainty about disease trajectory and treatment outcomes generates chronic psychological strain, particularly in older adults. Caregivers report high emotional burden, social withdrawal, and diminished well-being. Despite growing recognition of these issues, systematic psychosocial screening and targeted interventions remain rare in routine nephrology. Conclusions: This review highlights loneliness and uncertainty as silent but modifiable risk factors in CKD, on par with traditional biomedical markers. We argue that nephrology urgently requires a shift toward a biopsychosocial model of care that includes structured emotional screening, culturally responsive interventions, and caregiver support. By reframing psychosocial suffering as a clinical priority rather than a secondary concern, nephrology can move toward more person-centered and equitable care.
Background: Metabolic Syndrome (MetS), associated with hyperinsulinemia and insulin resistance, represents a significant global health concern Objective: This study aimed to explore the epidemiology o...
Background: Metabolic Syndrome (MetS), associated with hyperinsulinemia and insulin resistance, represents a significant global health concern Objective: This study aimed to explore the epidemiology of MetS in Western Sudan Methods: This study is a cross-sectional clinic-based investigation conducted at Prof. Medical Complex in Prof. Medical Research Consultancy Center (Prof. MRCC) located in El-Obeid city, the capital of North Kordofan State, Sudan, covering the period from January 1, 2025, to April 3, 2026. We applied the International Diabetes Federation (IDF) criteria for diagnosing MetS. Results: Men made up 56% of the total, whereas women accounted for 44%. The analysis of waist circumference (WC) among participants, alongside high-density lipoprotein cholesterol (HDL-C) and triglyceride (TG) levels, revealed that 5.7% exhibited abnormalities indicative of metabolic syndrome. Additionally, 28.6% had low HDL-C levels coupled with high TG levels, while 12.4% presented with low HDL levels and elevated WC. Individuals exhibiting elevated TG levels and high WC constituted 7.5% of individuals. The relationship between male sex and the risk of low HDL-C is demonstrated by a relative risk (RR) of 1.385, with a 95% confidence interval (95% CI) spanning from 1.178 to 1.628 and a P-value of <.001. Conclusions: The prevalence of MetS in Western Sudan was 5.7%, with a notably higher rate observed in males. The prevalence of low HDL-C levels surpassed global averages, although it was marginally lower than findings from sub-Saharan Africa. Hypertriglyceridemia levels aligned with sub-Saharan data and were slightly elevated compared to the global range. The findings underscore the necessity for public health interventions, particularly in promoting regular physical activity and encouraging healthy dietary habits.
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