Category: Statistics

Phys Rev Lett. 2024 Oct 4;133(14):147101. doi: 10.1103/PhysRevLett.133.147101.

ABSTRACT

A simple model of charge transport is provided by a classical particle in a random potential and a dissipative coupling to the environment. The corresponding nonequilibrium steady state (NESS) can be determined analytically when both the disorder and dissipation are weak. We use it to illuminate some foundational issues in nonequilibrium statistical mechanics. We show that at nonlinear level dissipative response sensitively depends on the system-environment coupling, and the range of validity of the linear response theory is set by this coupling. This validates the Van Kampen objection. We also show that the principle of minimum entropy production does not determine the NESS beyond linear order in the electric field, while entropy maximization fails to produce the correct NESS already at linear order.

PMID:39423393 | DOI:10.1103/PhysRevLett.133.147101

Phys Rev Lett. 2024 Oct 4;133(14):148301. doi: 10.1103/PhysRevLett.133.148301.

ABSTRACT

Confining in space the equilibrium fluctuations of statistical systems with long-range correlations is known to result into effective forces on the boundaries. Here we demonstrate the occurrence of Casimir-like forces in the nonequilibrium context provided by flocking active matter. In particular, we consider a system of aligning self-propelled particles in two spatial dimensions that are transversally confined by reflecting or partially reflecting walls. We show that in the ordered flocking phase this confined active vectorial fluid is characterized by extensive boundary layers, as opposed to the finite ones usually observed in confined scalar active matter. Moreover, a finite-size, fluctuation-induced contribution to the pressure on the wall emerges, which decays slowly and algebraically upon increasing the distance between the walls. We explain our findings-which display a certain degree of universality-within a hydrodynamic description of the density and velocity fields.

PMID:39423381 | DOI:10.1103/PhysRevLett.133.148301

Phys Rev Lett. 2024 Oct 4;133(14):146604. doi: 10.1103/PhysRevLett.133.146604.

ABSTRACT

Demonstrating the non-Abelian Ising anyon statistics of Majorana zero modes in a physical platform still represents a major open challenge in physics. We here show that the linear low-frequency charge conductance of a Majorana interferometer containing a floating superconducting island can reveal the topological spin of quantum edge vortices. The latter are associated with chiral Majorana fermion edge modes and represent “flying” Ising anyons. We describe possible device implementations and outline how to detect non-Abelian anyon braiding through ac conductance measurements.

PMID:39423376 | DOI:10.1103/PhysRevLett.133.146604

J Med Internet Res. 2024 Oct 18;26:e54135. doi: 10.2196/54135.

ABSTRACT

BACKGROUND: The internet has become an increasingly vital platform for health-related information, especially in upper-middle-income countries such as China. While previous research has suggested that online health information seeking (OHIS) can significantly impact individuals’ engagement in health behaviors, most research focused on patient-centered health communication.

OBJECTIVE: This study aims to examine how OHIS influences health behavior engagement among Chinese internet users, focusing on the role of eHealth literacy and perceived information quality in influencing relationships.

METHODS: An online cross-sectional survey was conducted in November 2021 among 10,000 Chinese internet users, using quota sampling based on sex, age, and urban and rural residence, in line with the 48th Statistical Report on Internet Development of China. Nonparametric tests were used to examine the differences in eHealth literacy across sociodemographic groups. Partial correlation analysis and stepwise linear regression were conducted to test the associations between key variables. Confirmatory factor analysis and structural equation modeling were conducted to test the hypotheses.

RESULTS: Our study identified significant disparities in functional and critical eHealth literacy between urban and rural residents across age groups, income levels, education backgrounds, and health conditions (all P<.001). In terms of sex and regional differences, we found higher functional literacy among female users than male users, and critical literacy varied significantly across different regions. The proposed structural model showed excellent fit (χ²₄₀₄=4183.6, χ²₄₀₄=10.4,P<.001; root mean square error of approximation value of 0.031, 95% CI 0.030-.031; standardized root mean square residual value of 0.029; and comparative fit index value of 0.955), highlighting reciprocal associations between 2 types of eHealth literacy and OHIS. Participants’ functional eHealth literacy, critical eHealth literacy, and OHIS have positive impacts on their health behavioral engagement. Perceived information quality was found to mediate the influence of OHIS on health behavior (b=0.003, 95% CI 0.002-0.003; P<.001).

CONCLUSIONS: The study revealed the pathways linking sociodemographic factors, eHealth literacy, OHIS, and perceived information quality and how they together influenced health outcomes. The findings underscore the significance of enhancing eHealth literacy and improving information quality to promote better health outcomes among Chinese internet users.

PMID:39423374 | DOI:10.2196/54135

JMIR Res Protoc. 2024 Oct 18;13:e60719. doi: 10.2196/60719.

ABSTRACT

BACKGROUND: The prevalence of heart failure (HF) is increasing worldwide, with the associated mortality rates rising consistently. Preventing HF progression requires adherence to restricted sodium intake alongside sufficient and balanced nutritional consumption. For patients at home, preparing nutritionally balanced meals is essential, either self-assisted or with the aid of close individuals. Patients with HF frequently experience decreased exercise tolerance, depression, anxiety, and social isolation, which interfere with eating behaviors, leading to inadequate dietary habits. However, measures focusing on the determinants of eating behavior among patients with HF are currently lacking.

OBJECTIVE: This study aims to develop a self-administered scale to assess the eating behaviors of patients with HF living at home (Self-Administered Eating Behaviors Scale for Heart Failure [SEBS-HF]).

METHODS: This study encompasses 3 phases. Phase 1 involves identifying factors influencing eating behaviors in patients with HF. First, a literature review will be conducted using PubMed and CINAHL databases. The specified literature will be analyzed qualitatively and inductively. Additionally, verbatim transcripts obtained from semistructured interviews of patients with HF and medical experts will be qualitatively analyzed. Based on the Phase 1 results, a preliminary scale will be constructed. In Phase 2, cognitive interviews will be conducted with patients with HF and experts; the preliminary scale will be used to qualitatively evaluate its content validity. After validation, the scale will be used in Phase 3 to conduct a cross-sectional study involving patients with HF. In Phase 3, data will be collected from clinical records and self-administered questionnaires or scales. After conducting a preliminary survey, the main survey will be conducted. The reliability and validity of the scale will be assessed using statistical methods.

RESULTS: The first phase of this study commenced in September 2023, and by May 2, 2024, a total of 7 patients with HF and 6 expert professionals were enrolled as study participants. The draft creation of the scale will be completed in 2024, and the content validity evaluation of the draft scale is expected to be finished by early 2025. The third phase will begin its investigation in mid-2025 and is expected to be completed by late 2025, after which the SEBS-HF will be published.

CONCLUSIONS: The development and use of this scale will enable a more comprehensive evaluation of the factors influencing eating behaviors in patients with HF. Thus, medical and welfare professionals should provide appropriate support tailored to the specific needs of patients with HF.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/60719.

PMID:39423373 | DOI:10.2196/60719

J Med Internet Res. 2024 Oct 18;26:e43954. doi: 10.2196/43954.

ABSTRACT

BACKGROUND: Remote measurement technology (RMT) involves the use of wearable devices and smartphone apps to measure health outcomes in everyday life. RMT with feedback in the form of data visual representations can facilitate self-management of chronic health conditions, promote health care engagement, and present opportunities for intervention. Studies to date focus broadly on multiple dimensions of service users’ design preferences and RMT user experiences (eg, health variables of perceived importance and perceived quality of medical advice provided) as opposed to data visualization preferences.

OBJECTIVE: This study aims to explore data visualization preferences and priorities in RMT, with individuals living with depression, those with epilepsy, and those with multiple sclerosis (MS).

METHODS: A triangulated qualitative study comparing and thematically synthesizing focus group discussions with user reviews of existing self-management apps and a systematic review of RMT data visualization preferences. A total of 45 people participated in 6 focus groups across the 3 health conditions (depression, n=17; epilepsy, n=11; and MS, n=17).

RESULTS: Thematic analysis validated a major theme around design preferences and recommendations and identified a further four minor themes: (1) data reporting, (2) impact of visualization, (3) moderators of visualization preferences, and (4) system-related factors and features.

CONCLUSIONS: When used effectively, data visualizations are valuable, engaging components of RMT. Easy to use and intuitive data visualization design was lauded by individuals with neurological and psychiatric conditions. Apps design needs to consider the unique requirements of service users. Overall, this study offers RMT developers a comprehensive outline of the data visualization preferences of individuals living with depression, epilepsy, and MS.

PMID:39423366 | DOI:10.2196/43954

Cancer Rep (Hoboken). 2024 Oct;7(10):e70026. doi: 10.1002/cnr2.70026.

ABSTRACT

BACKGROUND AND AIM: Delay in diagnosis and treatment of lung cancer is thought to be a major cause of its poor outcomes. We evaluated the delays within the presentation to the initiation of diagnostic and therapeutic interventions amongst lung cancer patients in Southern Iran.

METHODS: This cross-sectional study was conducted from March 2019 to March 2021. The data collected through interview included socio-demographic, medical and clinical findings, and the time intervals needed to visit physician, refer to specialist, request diagnostic procedures, reach diagnosis of lung cancer, and hospitalization.

RESULTS: Eighty-nine patients (58 males and 31 females) with a mean age of 61.01 ± 12.25 years were included. The median time of symptom presentation and first physician visit interval was 25 days. Sixty-five days were spent for requesting, performing, and evaluating the diagnostic procedures. The median interval between diagnosis and initiation of treatment was 16 days. Totally, it took an average of 122 days from the presentation to the definite diagnosis of lung cancer. Patient-, diagnosis-, and treatment-related delays were not significantly correlated with any of the demographic, socioeconomic, and clinical (disease stage, symptom) variables, as well as the diagnosis tool and the first physician who visited the patient (p > 0.05).

CONCLUSIONS: There was a significant delay but relatively similar to other countries in the diagnosis and treatment of lung cancer patients in Southern Iran. The largest portion of delay could be attributed to the raising clinical suspicion in the physicians, referral for diagnostic assessments, and the diagnosis process.

PMID:39423347 | DOI:10.1002/cnr2.70026

JMIR Med Inform. 2024 Oct 18;12:e57569. doi: 10.2196/57569.

ABSTRACT

BACKGROUND: Reaching meaningful interoperability between proprietary health care systems is a ubiquitous task in medical informatics, where communication servers are traditionally used for referring and transforming data from the source to target systems. The Mirth Connect Server, an open-source communication server, offers, in addition to the exchange functionality, functions for simultaneous manipulation of data. The standard Fast Healthcare Interoperability Resources (FHIR) has recently become increasingly prevalent in national health care systems. FHIR specifies its own standardized mechanisms for transforming data structures using StructureMaps and the FHIR mapping language (FML).

OBJECTIVE: In this study, a generic approach is developed, which allows for the application of declarative mapping rules defined using FML in an exchangeable manner. A transformation engine is required to execute the mapping rules.

METHODS: FHIR natively defines resources to support the conversion of instance data, such as an FHIR StructureMap. This resource encodes all information required to transform data from a source system to a target system. In our approach, this information is defined in an implementation-independent manner using FML. Once the mapping has been defined, executable Mirth channels are automatically generated from the resources containing the mapping in JavaScript format. These channels can then be deployed to the Mirth Connect Server.

RESULTS: The resulting tool is called FML2Mirth, a Java-based transformer that derives Mirth channels from detailed declarative mapping rules based on the underlying StructureMaps. Implementation of the translate functionality is provided by the integration of a terminology server, and to achieve conformity with existing profiles, validation via the FHIR validator is built in. The system was evaluated for its practical use by transforming Labordatenträger version 2 (LDTv.2) laboratory results into Medical Information Object (Medizinisches Informationsobjekt) laboratory reports in accordance with the National Association of Statutory Health Insurance Physicians’ specifications and into the HL7 (Health Level Seven) Europe Laboratory Report. The system could generate complex structures, but LDTv.2 lacks some information to fully comply with the specification.

CONCLUSIONS: The tool for the auto-generation of Mirth channels was successfully presented. Our tests reveal the feasibility of using the complex structures of the mapping language in combination with a terminology server to transform instance data. Although the Mirth Server and the FHIR are well established in medical informatics, the combination offers space for more research, especially with regard to FML. Simultaneously, it can be stated that the mapping language still has implementation-related shortcomings that can be compensated by Mirth Connect as a base technology.

PMID:39423342 | DOI:10.2196/57569

Prehosp Emerg Care. 2024 Oct 18:1-11. doi: 10.1080/10903127.2024.2417842. Online ahead of print.

ABSTRACT

OBJECTIVES: The objective of this quality improvement (QI) study was to improve organizational learning from clinical debriefs known as ‘Coffee and Cases’ (C&C) in a helicopter emergency medical service (HEMS) by increasing weekly learning summaries (LS) and documented learning points (DLP) as well as the dissemination thereof by at least 50% from baseline.

METHODS: The problem analysis for sub-optimal organizational learning from C&C identified several factors, including lack of responsibility, poor documentation quality, and limited sharing of learning points. Using the Model for Improvement (MFI), interventions enhanced the learning environment, and improved documentation and dissemination. Changes included dedicated computers, introducing standardized processes, a newsletter and searchable DLP database. Statistical process control (SPC) charts were used to assess the effectiveness of interventions.

RESULTS: Prior to interventions (August 2022 to January 2023), baseline mean counts of weekly DLPs, LSs, DLPs internally disseminated, and DLPs openly disseminated were 3.18, 2.67, 3.18, and 2.96, respectively. Plan-Do-Study-Act (PDSA) cycles included declaring C&C as a non-clinical portfolio, redesigning documentation processes, initiating monthly newsletters, developing a DLP repository, and designing a C&C visual brand. Signals of special cause variation showed improvements, with mean counts increasing. Weekly DLPs increased to 14.92, LSs to 5.2, internally disseminated C&C Snippets to 11.88, and openly disseminated C&C Snippets to 8.64.

CONCLUSIONS: Recognizing barriers to effective knowledge creation and sharing, our QI study aimed to increase weekly DLPs and LSs by 50% from baseline. It aligned with the relationship between knowledge management and organizational learning, emphasizing the importance of utilizing knowledge for improved performance. Our interventions enhanced the learning environment, ensured robust capturing of learning points and effective communication thereof, ultimately contributing towards improving organizational dissemination of learning from clinical debriefs. Our QI study demonstrates how enhanced knowledge creation and sharing can widen the benefits of learning from clinical team debriefs.

PMID:39423335 | DOI:10.1080/10903127.2024.2417842

Brain. 2024 Oct 18:awae316. doi: 10.1093/brain/awae316. Online ahead of print.

ABSTRACT

Accelerated long-term forgetting (ALF) is the phenomenon whereby material is retained normally over short intervals (e.g. minutes) but forgotten abnormally rapidly over longer periods (days or weeks). ALF may be an early marker of cognitive decline, but little is known about its relationships with preclinical Alzheimer’s disease pathology, and how memory selectivity may influence which material is forgotten. We assessed ALF in ‘Insight 46’, a sub-study of the MRC National Survey of Health and Development (a population-based cohort born during one week in 1946) (n=429; 47% female; assessed aged ∼73 years). ALF assessment comprised visual and verbal memory tests: Complex Figure Drawing and the Face-Name Associative Memory Exam (FNAME). ALF scores were calculated as the percentage of material retained after 7 days, relative to 30 minutes. In 306 cognitively-normal participants, we investigated effects on ALF of β-amyloid pathology (quantified using 18F-Florbetapir-PET, classified as positive/negative) and whole-brain and hippocampal atrophy rate (quantified from serial T1-MRI over ∼2.4 years preceding the ALF assessment), as well as interactions between these pathologies. We categorized Complex Figure Drawing items as ‘outline’ or ‘detail’, to test our hypothesis that forgetting the outline of the structure would be more sensitive to the effect of brain pathologies. We also investigated associations between ALF and Subjective Cognitive Decline, measured with the MyCog questionnaire. Complex Figure ‘outline’ items were better retained than ‘detail’ items (mean retention over 7 days = 94% vs 72%). Amyloid-positive participants showed greater forgetting of the Complex Figure outline, compared to amyloid-negatives (90% vs 95%; P<0.01). There were interactions between amyloid pathology and cerebral atrophy, such that whole-brain and hippocampal atrophy predicted greater ALF on Complex Figure Drawing among amyloid-positives only (e.g. 1.9 percentage-points lower retention per ml/year of whole-brain atrophy [95% confidence intervals 0.5, 3.7]; P<0.05). Greater ALF on FNAME was associated with increased rate of hippocampal atrophy. ALF on Complex Figure Drawing also correlated with subjective cognitive decline (-0.45 percentage-points per MyCog point [-0.85, -0.05], P<0.05). These results provide evidence of associations between some measures of ALF and biomarkers of brain pathologies and subjective cognitive decline in cognitively-normal older adults. On Complex Figure Drawing, ‘outline’ items were better remembered than ‘detail’ items – illustrating the strategic role of memory selectivity – but ‘outline’ items were also relatively more vulnerable to ALF in individuals with amyloid pathology. Overall, our findings suggest that ALF may be a sensitive marker of cognitive changes in preclinical Alzheimer’s disease.

PMID:39423292 | DOI:10.1093/brain/awae316