bluuebunny/crossref_metadata_2025_split huggingface dataset:
Applying the UTAUT2 framework to patients’ attitudes toward healthcare task shifting with artificial intelligence
Authors: Huang Weiting , Ong Wen Chong , Wong Mark Kei Fong , Ng Eddie Yin Kwee , Koh Tracy , Chandramouli Chanchal , Ng Choon Ta , Hummel Yoran , Huang Feiqiong , Lam Carolyn Su Ping , Tromp Jasper 
Published: April 2024

Abstract
Background
Increasing patient loads, healthcare inflation and ageing population have put pressure on the healthcare system. Artificial intelligence and machine learning innovations can aid in task shifting to help healthcare systems remain efficient and cost effective. To gain an understanding of patients’ acceptance toward such task shifting with the aid of AI, this study adapted the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), looking at performance and effort expectancy, facilitating conditions, social influence, hedonic motivation and behavioural intention.

Methods
This was a cross-sectional study which took place between September 2021 to June 2022 at the National Heart Centre, Singapore. One hundred patients, aged ≥ 21 years with at least one heart failure symptom (pedal oedema, New York Heart Association II-III effort limitation, orthopnoea, breathlessness), who presented to the cardiac imaging laboratory for physician-ordered clinical echocardiogram, underwent both echocardiogram by skilled sonographers and the experience of echocardiogram by a novice guided by AI technologies. They were then given a survey which looked at the above-mentioned constructs using the UTAUT2 framework.

Results
Significant, direct, and positive effects of all constructs on the behavioral intention of accepting the AI-novice combination were found. Facilitating conditions, hedonic motivation and performance expectancy were the top 3 constructs. The analysis of the moderating variables, age, gender and education levels, found no impact on behavioral intention.

Conclusions
These results are important for stakeholders and changemakers such as policymakers, governments, physicians, and insurance companies, as they design adoption strategies to ensure successful patient engagement by focusing on factors affecting the facilitating conditions, hedonic motivation and performance expectancy for AI technologies used in healthcare task shifting.
Geographic and socioeconomic inequalities in the coverage of contraception in Uttar Pradesh, India
Authors: Halli Shiva S , Alam Mohd Tauheed , Namasivayam Vasanthakumar , Prakash Ravi , Anand Preeti , Blanchard James , Wehrmeister Fernando 
Published: April 2024

Abstract
Background
Uttar Pradesh (UP) is the most populous state in India, with a historically lower level of family planning coverage than the national average. In recent decades, family planning coverage in UP has significantly increased, yet there are considerable geographic and socio-economic inequalities.

Methods
The data used for the study is derived from a cross-sectional quantitative survey of 12,200 currently married women conducted during December 2020–February 2021 in UP by the Technical Support Unit. Univariate and bivariate analyses were performed and equiplots were used to make visualizing inequalities easy.

Results
The findings of the study reveal significant variation in family planning coverage indicators amongst currently married women in reproductive ages by administrative divisions in UP. For instance, in the Jhansi division, it was 72.4%, while in Faizabad, it was 39.3%. Jhansi division experienced the highest modern contraceptive coverage with the lowest inequity compared to other divisions. However, the range of coverage within the division by Accredited Social Health Activist (ASHA) areas is 25% to 75%. In fact, for some ASHA areas in the Jhansi division, the family planning demand satisfied for modern contraception ranged from more than 85% to less than 22%. On the other hand, the Gonda division with the lowest coverage and lowest inequity for demand satisfied for modern contraception has some ASHA areas with less than 5% and some with more than 36%. The study also revealed intersectionality of education, wealth, place of residence and geographic divisions in identifying inequity patterns. For instance, in case of Mirzapur and Varanasi, the demand satisfied among the illiterates was 69% and the corresponding percentage for literates was 49%. With respect to place of residence, Basti division, where the coverage for modern contraception is extremely low, demand satisfied for modern contraceptive methods is 16.3% among rural residents compared to 57.9% in the case of urban residents.

Conclusions
The findings showed inequality in the modern family planning methods coverage in UP in both best and worst performing divisions. The inequalities exist even in extremely small geographies such as ASHA areas. Within the geographies as well, the socio-economic inequalities persisted. These inequalities at multiple levels are important to consider for effective resource allocation and utilization.
Diagnostic delay of sarcoidosis: an integrated systematic review
Authors: Namsrai Tergel , Phillips Christine , Parkinson Anne , Gregory Dianne , Kelly Elaine , Cook Matthew , Desborough Jane 
Published: April 2024

Abstract
Background
Sarcoidosis is a chronic inflammatory granulomatous disease of unknown cause. Delays in diagnosis can result in disease progression and poorer outcomes for patients. Our aim was to review the current literature to determine the overall diagnostic delay of sarcoidosis, factors associated with diagnostic delay, and the experiences of people with sarcoidosis of diagnostic delay.

Methods
Three databases (PubMed/Medline, Scopus, and ProQuest) and grey literature sources were searched. Random effects inverse variance meta-analysis was used to pool mean diagnostic delay in all types of sarcoidosis subgroup analysis. Diagnostic delay was defined as the time from reported onset of symptoms to diagnosis of sarcoidosis.

Results
We identified 374 titles, of which 29 studies were included in the review, with an overall sample of 1531 (694 females, 837 males). The overall mean diagnostic delay in all types of sarcoidosis was 7.93 months (95% CI 1.21 to 14.64 months). Meta-aggregation of factors related to diagnostic delay in the included studies identified three categories: (1) the complex and rare features of sarcoidosis, (2) healthcare factors and (3) patient-centred factors. Meta-aggregation of outcomes reported in case studies revealed that the three most frequent outcomes associated with diagnostic delay were: (1) incorrect diagnosis, (2) incorrect treatment and (3) development of complications/disease progression. There was no significant difference in diagnostic delay between countries with gatekeeper health systems (where consumers are referred from a primary care clinician to specialist care) and countries with non-gatekeeper systems. No qualitative studies examining people’s experiences of diagnostic delay were identified.

Conclusion
The mean diagnostic delay for sarcoidosis is almost 8 months, which has objective consequences for patient management. On the other hand, there is a paucity of evidence about the experience of diagnostic delay in sarcoidosis and factors related to this. Gaining an understanding of people’s experiences while seeking a diagnosis of sarcoidosis is vital to gain insight into factors that may contribute to delays, and subsequently inform strategies, tools and training activities aimed at increasing clinician and public awareness about this rare condition.

Trial registration
PROSPERO Registration number: CRD42022307236.
Minimal clinically important differences in six-minute walking distance in late-onset Pompe disease
Authors: Claeys Kristl G. , Kushlaf Hani , Raza Syed , Hummel Noemi , Shohet Simon , Keyzor Ian , Kopiec Agnieszka , Graham Ryan , Fox Brian , Schoser Benedikt 
Published: April 2024

Abstract
Background
The minimal clinically important difference (MCID) is the smallest change in outcome that physicians or patients would consider meaningful and is relevant when evaluating disease progression or the efficacy of interventions. Studies of patients with late-onset Pompe disease (LOPD) have used the 6-min walk distance (6MWD) as an endpoint to assess motor function. However, an MCID for 6MWD (% predicted and meters) has yet to be established in LOPD. The objective of the study was to derive 6MWD MCID (% predicted and meters) with different analysis methods and for subgroups of different disease severity for LOPD.

Methods
Data from the PROPEL trial were used to calculate 6MWD MCID in the overall PROPEL population and subgroups of baseline severity as assessed by walking distance and body mass index (BMI), using anchor- and distribution-based approaches.

Results
The 6MWD MCIDs varied widely, depending on the method and subgroup, ranging from 2.27%-8.11% predicted for the overall LOPD population (23.7 m-57.2 m). For patients with baseline 6MWD < 150 m, MCIDs ranged from -0.74%-3.37% (-2.1 m-11.3 m). MCIDs increased with distance walked at baseline until a plateau was reached. For BMI subgroups, the MCIDs were generally lowest in obese patients.

Conclusion
Our analysis shows that MCID depends on the chosen method and disease severity. The findings suggest that applying a single MCID to all patients can be misleading; consequently, a range of possible MCIDs should be considered. This may also be highly relevant for other neuromuscular diseases. This study provides a range of 6MWD MCIDs for LOPD, with lower MCIDs for more severe patients.
The 37TrillionCells initiative for improving global healthcare via cell-based interception and precision medicine: focus on neurodegenerative diseases
Authors: Coulombe Benoit , Durcan Thomas M. , Bernard Geneviève , Moursli Asmae , Poitras Christian , Faubert Denis , Pinard Maxime 
Published: April 2024

AbstractOne of the main burdens in the treatment of diseases is imputable to the delay between the appearance of molecular dysfunctions in the first affected disease cells and their presence in sufficient number for detection in specific tissues or organs. This delay obviously plays in favor of disease progression to an extent that makes efficient treatments difficult, as they arrive too late. The development of a novel medical strategy, termed cell-based interception and precision medicine, seeks to identify dysfunctional cells early, when tissue damages are not apparent and symptoms not yet present, and develop therapies to treat diseases early. Central to this strategy is the use of single-cell technologies that allow detection of molecular changes in cells at the time of phenotypical bifurcation from health to disease. In this article we describe a general procedure to support such an approach applied to neurodegenerative disorders. This procedure combines four components directed towards highly complementary objectives: 1) a high-performance single-cell proteomics (SCP) method (Detect), 2) the development of disease experimental cell models and predictive computational models of cell trajectories (Understand), 3) the discovery of specific targets and personalized therapies (Cure), and 4) the creation of a community of collaborating laboratories to accelerate the development of this novel medical paradigm (Collaborate). A global initiative named 37TrillionCells (37TC) was launched to advance the development of cell-based interception and precision medicine.
Scoary2: rapid association of phenotypic multi-omics data with microbial pan-genomes
Authors: Roder Thomas , Pimentel Grégory , Fuchsmann Pascal , Stern Mireille Tena , von Ah Ueli , Vergères Guy , Peischl Stephan , Brynildsrud Ola , Bruggmann Rémy , Bär Cornelia 
Published: April 2024

AbstractUnraveling bacterial gene function drives progress in various areas, such as food production, pharmacology, and ecology. While omics technologies capture high-dimensional phenotypic data, linking them to genomic data is challenging, leaving 40–60% of bacterial genes undescribed. To address this bottleneck, we introduce Scoary2, an ultra-fast microbial genome-wide association studies (mGWAS) software. With its data exploration app and improved performance, Scoary2 is the first tool to enable the study of large phenotypic datasets using mGWAS. As proof of concept, we explore the metabolome of yogurts, each produced with a different Propionibacterium reichii strain and discover two genes affecting carnitine metabolism.
Effectiveness of personalized meal recommendation in improving dietary behaviors of Chinese community-dwelling elders: study protocol for a cluster randomized controlled trial
Authors: Xu Zidu , Xu Xiaowei , Sun Lianglong , Guo Zhen , Lai Jianqiang , Kang Lin , Li Jiao 
Published: April 2024

Abstract
Background
Inappropriate eating behaviors, particularly a lack of food diversity and poor diet quality, have a significant impact on the prognosis of certain chronic conditions and exacerbate these conditions in the community-dwelling elderly population. Current dietary interventions for the elderly have not adequately considered the nutritional needs associated with multiple chronic conditions and personal dietary preferences of elderly individuals. A personalized recommendation system has been recognized as a promising approach to address this gap. However, its effectiveness as a component of an elderly-targeted dietary intervention in real-world settings remains unknown. Additionally, it is unclear whether this intervention approach will be user-friendly for the elderly. Therefore, this study aims to examine the effectiveness of a personalized meal recommendation system designed to improve dietary behavior in community-dwelling elders. The implementation process in terms of System usability and satisfaction will also be assessed.

Methods
The trial has been designed as a 6-month, non-blinded, parallel two-arm trial. One hundred fifty community-dwelling elders who meet the eligibility criteria will be enrolled. Subjects will be allocated to either the intervention group, receiving personalized meal recommendations and access to corresponding food provided as one component of the intervention, as well as health education on elder nutrition topics, or the control group, which will receive nutritional health education lectures. Outcomes will be measured at three time points: baseline at 0 months, 3 months, and 6 months. The primary outcomes will include dietary diversity (DDS) and diet quality (CDGI-E) of enrolled community-dwelling elders, representing their dietary behavior improvement, along with dietary behavior adherence to recommended meals. Secondary outcomes will measure the perceived acceptability and usability of the personalized meal recommendation system for the intervention group. Exploratory outcomes will include changes in the nutritional status and anthropometric measurements of the community-dwelling elders.

Discussion
This study aims to examine the effectiveness, acceptability, and usability of a personalized meal recommendation system as a data-driven dietary intervention to benefit community-dwelling elders. The successful implementation will inform the future development and integration of digital health strategies in daily nutrition support for the elderly.

Trial registration
Chinese Clinical Trial Registry ChiCTR2300074912. Registered on August 20, 2023, https://www.chictr.org.cn/showproj.html?proj=127583
High temperatures and low humidity promote the occurrence of microsporidians (Microsporidia) in mosquitoes (Culicidae)
Authors: Trzebny Artur , Nahimova Olena , Dabert Miroslawa 
Published: April 2024

Abstract
Background
In the context of climate change, a growing concern is that vector-pathogen or host-parasite interactions may be correlated with climatic factors, especially increasing temperatures. In the present study, we used a mosquito-microsporidian model to determine the impact of environmental factors such as temperature, humidity, wind and rainfall on the occurrence rates of opportunistic obligate microparasites (Microsporidia) in hosts from a family that includes important disease vectors (Culicidae).

Methods
In our study, 3000 adult mosquitoes collected from the field over 3 years were analysed. Mosquitoes and microsporidia were identified using PCR and sequencing of the hypervariable V5 region of the small subunit ribosomal RNA gene and a shortened fragment of the cytochrome c oxidase subunit I gene, respectively.

Results
DNA metabarcoding was used to identify nine mosquito species, all of which were hosts of 12 microsporidian species. The prevalence of microsporidian DNA across all mosquito samples was 34.6%. Microsporidian prevalence in mosquitoes was more frequent during warm months (> 19 °C; humidity < 65%), as was the co-occurrence of two or three microsporidian species in a single host individual. During warm months, microsporidian occurrence was noted 1.6-fold more often than during the cold periods. Among the microsporidians found in the mosquitoes, five (representing the genera Enterocytospora, Vairimorpha and Microsporidium) were positively correlated with an increase in temperature, whereas one (Hazardia sp.) was significantly correlated with a decrease in temperature. Threefold more microsporidian co-occurrences were recorded in the warm months than in the cold months.

Conclusions
These results suggest that the susceptibility of mosquitoes to parasite occurrence is primarily determined by environmental conditions, such as, for example, temperatures > 19 °C and humidity not exceeding 62%. Collectively, our data provide a better understanding of the effects of the environment on microsporidian-mosquito interactions.

Graphical Abstract
PySmooth: a Python tool for the removal and correction of genotyping errors
Authors: Soibam Benjamin , Roman Gregg 
Published: April 2024

Abstract
Summary
In genetic mapping studies involving many individuals, genome-wide markers such as single nucleotide polymorphisms (SNPs) can be detected using different methods. However, it comes with some errors. Some SNPs associated with diseases can be in regions encoding long noncoding RNAs (lncRNAs). Therefore, identifying the errors in genotype file and correcting them is crucial for accurate genetic mapping studies. We develop a Python tool called PySmooth, that offers an easy-to-use command line interface for the removal and correction of genotyping errors. PySmooth uses the approach of a previous tool called SMOOTH with some modifications. It inputs a genotype file, detects errors and corrects them. PySmooth provides additional features such as imputing missing data, better user-friendly usage, generates summary and visualization files, has flexible parameters, and handles more genotype codes.

Availability and implementation
PySmooth is available at https://github.com/lncRNAAddict/PySmooth.
Assessing lava flow susceptibility at neighbouring volcanoes: Nyamulagira and Nyiragongo volcanoes, Virunga Volcanic Province
Authors: Kervyn M. , Barette F. , Poppe S. , Smets B. , Syavulisembo Muhindo A. , Kambale Makundi J. , Ngunzi Kahashi Y. , Kambale Ndagana J. , Mossoux S. , Kervyn F. , Michellier C. 
Published: April 2024

AbstractAssessing volcanic hazards in locations exposed to multiple central volcanoes requires to consider multiple potential eruption sources and their respective characteristics. While this is common practice in ashfall hazard assessment, this is generally not considered for topography-controlled volcanic flow processes. Yet, in volcanic areas with closely spaced volcanic systems, eruptions fed from several contrasted volcanic systems might threaten one given area. Considering the case of the Nyiragongo and Nyamulagira volcanoes in the Virunga Volcanic Province (D.R.Congo), we present a method to produce a combined lava flow inundation susceptibility map that integrates both volcanoes. The spatial distribution of the probability of vent opening for the next eruption is separately constrained for both volcanoes based on the mapping of historical and pre-historical eruptive vents and fissures. The Q-LavHa lava flow probability model is then calibrated separately for each volcano, considering several historical lava flows of Nyamulagira (2004, 2006, 2010) and Nyiragongo (2002). The maps for the two volcanoes are thereafter integrated based on a weighted sum of both individual lava flow inundation probability maps, assuming historically-based relative eruption frequency of the two volcanoes. The accuracy of this probabilistic susceptibility map for the most active volcanic region in Africa was unfortunately validated by the May 2021 lava flow produced by Nyiragongo. This map was discussed and validated in 2019 with local scientists, as well as representatives of disaster management and urban planning institutions, but was not included in the regional contingency plan ahead of the 2021 eruption crisis. Updating the volcanic crisis and evacuation management plans with this lava flow probability map could contribute to reinforce risk awareness among the population and inform the future development of the city of Goma.
Blow up, growth, and decay of solutions for a class of coupled nonlinear viscoelastic Kirchhoff equations with distributed delay and variable exponents
Authors: Boulaaras Salah , Choucha Abdelbaki , Ouchenane Djamel , Jan Rashid 
Published: April 2024

AbstractIn this work, we consider a quasilinear system of viscoelastic equations with dispersion, source, distributed delay, and variable exponents. Under a suitable hypothesis the blow-up and growth of solutions are proved, and by using an integral inequality due to Komornik the general decay result is obtained in the case of absence of the source term $f_{1}=f_{2}=0$

f
1

=

f
2

=
0
.
Teachers and educators’ experiences and perceptions of artificial-powered interventions for autism groups
Authors: Li Guang , Zarei Mohammad Amin , Alibakhshi Goudarz , Labbafi Akram 
Published: April 2024

Abstract
Background
Artificial intelligence-powered interventions have emerged as promising tools to support autistic individuals. However, more research must examine how teachers and educators perceive and experience these AI systems when implemented.

Objectives
The first objective was to investigate informants’ perceptions and experiences of AI-empowered interventions for children with autism. Mainly, it explores the informants’ perceived benefits and challenges of using AI-empowered interventions and their recommendations for avoiding the perceived challenges.

Methodology
A qualitative phenomenological approach was used. Twenty educators and parents with experience implementing AI interventions for autism were recruited through purposive sampling. Semi-structured and focus group interviews conducted, transcribed verbatim, and analyzed using thematic analysis.

Findings
The analysis identified four major themes: perceived benefits of AI interventions, implementation challenges, needed support, and recommendations for improvement. Benefits included increased engagement and personalized learning. Challenges included technology issues, training needs, and data privacy concerns.

Conclusions
AI-powered interventions show potential to improve autism support, but significant challenges must be addressed to ensure effective implementation from an educator’s perspective. The benefits of personalized learning and student engagement demonstrate the potential value of these technologies. However, with adequate training, technical support, and measures to ensure data privacy, many educators will likely find integrating AI systems into their daily practices easier.

Implications
To realize the full benefits of AI for autism, developers must work closely with educators to understand their needs, optimize implementation, and build trust through transparent privacy policies and procedures. With proper support, AI interventions can transform how autistic individuals are educated by tailoring instruction to each student’s unique profile and needs.