bluuebunny/crossref_metadata_2025_split huggingface dataset:
SCV Filter: A Hybrid Deep Learning Model for SARS-CoV-2 Variants
Classification
Authors: Wang Han , Gao Jingyang 
Published: November 2023

Background:
The high mutability of severe acute respiratory syndrome coronavirus
2(SARS-CoV-2) makes it easy for mutations to occur during transmission. As the epidemic continues to
develop, several mutated strains have been produced. Researchers worldwide are working on the effective identification of SARS-CoV-2.

Objective:
In this paper, we propose a new deep learning method that can effectively identify SARSCoV-2 Variant sequences, called SCVfilter, which is a deep hybrid model with embedding, attention
residual network, and long short-term memory as components.

Methods:
Deep learning is effective in extracting rich features from sequence data, which has significant implications for the study of Coronavirus Disease 2019 (COVID-19), which has become prevalent
in recent years. In this paper, we propose a new deep learning method that can effectively identify
SARS-CoV-2 Variant sequences, called SCVfilter, which is a deep hybrid model with embedding, attention residual network, and long short-term memory as components.

Results:
The accuracy of the SCVfilter is 93.833% on Dataset-I consisting of different variant strains;
90.367% on Dataset-II consisting of data collected from China, Taiwan, and Hong Kong; and 79.701%
on Dataset-III consisting of data collected from six continents (Africa, Asia, Europe, North America,
Oceania, and South America).

Conclusion:
When using the SCV filter to process lengthy and high-homology SARS-CoV-2 data, it
can automatically select features and accurately detect different variant strains of SARS-CoV-2. In addition, the SCV filter is sufficiently robust to handle the problems caused by sample imbalance and sequence incompleteness.

Other:
The SCVfilter is an open-source method available at https://github.com/deconvolutionw/SCVfilter.
Adoption of Electronic Health Record Among Substance Use Disorder Treatment Programs: Nationwide Cross-Sectional Survey Study
Authors: Frimpong Jemima A , Liu Xun , Liu Lingrui , Zhang Ruoqiuyan 
Published: November 2023

Background
Electronic health record (EHR) systems have been shown to be associated with improvements in care processes, quality of care, and patient outcomes. EHR also has a crucial role in the delivery of substance use disorder (SUD) treatment and is considered important for addressing SUD crises, including the opioid epidemic. However, little is known about the adoption of EHR in SUD treatment programs or the organizational-level factors associated with the adoption of EHR in SUD treatment.

Objective
We examined the adoption of EHR in SUD programs, with a focus on changes in adoption from 2014 to 2017, and identified organizational-level factors associated with EHR adoption.

Methods
We used data from the 2014 and 2017 National Drug Abuse Treatment System Surveys. Our analysis included 1027 SUD programs (531 in 2014 and 496 in 2017). We used chi-square and Mann-Whitney U tests for categorical and continuous variables, respectively, to assess changes in EHR adoption, technology use, program, and client characteristics. We also investigated differences in characteristics and barriers to adoption by EHR adoption status (adopted EHR vs had not adopted or were planning to adopt EHR). We then conducted multivariate logistic regressions to examine internal and external factors associated with EHR adoption.

Results
The adoption of EHR increased significantly from 57.6% (306/531) in 2014 to 69.2% (343/496) in 2017 (P<.001), showing that nearly one-third (153/496, 30.8%) of SUD programs had not yet adopted an EHR system by 2017. We identified a significant increase in technology use and ownership by a parent company (P=.01 and P<.001) and a decrease in the percentage of uninsured patients in 2017 (P<.001), compared to 2014. Our analysis further showed significant differences by adoption status for three major barriers to adoption: (1) start-up costs, (2) ongoing financial costs, and (3) privacy or security concerns (P<.001). Programs that used computerized scheduling (adjusted odds ratio [AOR] 3.02, 95% CI 2.23-4.09) and billing systems (AOR 2.29, 95% CI 1.62-3.25) were more likely to adopt EHR. Similarly, ownership type, such as private nonprofit (AOR 1.86, 95% CI 1.31-2.65) and public (AOR 2.14, 95% CI 1.27-3.67), or interest in participating in a patient-centered medical home (AOR 1.93, 95% CI 1.29-2.92), were associated with an increased likelihood to adopt EHR. Overall, SUD programs were more likely to adopt an EHR system in 2017 compared to 2014 (AOR 1.44, 95% CI 1.07-1.94).

Conclusions
Our findings highlighted that SUD programs may be on track to achieve widespread EHR adoption. However, there is a need for focused strategies, resources, and policies explicitly designed to systematically address barriers and tackle obstacles to expanding the adoption of EHR systems. These efforts must be holistic and address factors at multiple organizational levels.
The Roles of Electronic Health Records for Clinical Trials in Low- and Middle-Income Countries: Scoping Review
Authors: Ye Jiancheng , Xiong Shangzhi , Wang Tengyi , Li Jingyi , Cheng Nan , Tian Maoyi , Yang Yang 
Published: November 2023

Background
Clinical trials are a crucial element in advancing medical knowledge and developing new treatments by establishing the evidence base for safety and therapeutic efficacy. However, the success of these trials depends on various factors, including trial design, project planning, research staff training, and adequate sample size. It is also crucial to recruit participants efficiently and retain them throughout the trial to ensure timely completion.

Objective
There is an increasing interest in using electronic health records (EHRs)—a widely adopted tool in clinical practice—for clinical trials. This scoping review aims to understand the use of EHR in supporting the conduct of clinical trials in low- and middle-income countries (LMICs) and to identify its strengths and limitations.

Methods
A comprehensive search was performed using 5 databases: MEDLINE, Embase, Scopus, Cochrane Library, and the Cumulative Index to Nursing and Allied Health Literature. We followed the latest version of the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guideline to conduct this review. We included clinical trials that used EHR at any step, conducted a narrative synthesis of the included studies, and mapped the roles of EHRs into the life cycle of a clinical trial.

Results
A total of 30 studies met the inclusion criteria: 13 were randomized controlled trials, 3 were cluster randomized controlled trials, 12 were quasi-experimental studies, and 2 were feasibility pilot studies. Most of the studies addressed infectious diseases (15/30, 50%), with 80% (12/15) of them about HIV or AIDS and another 40% (12/30) focused on noncommunicable diseases. Our synthesis divided the roles of EHRs into 7 major categories: participant identification and recruitment (12/30, 40%), baseline information collection (6/30, 20%), intervention (8/30, 27%), fidelity assessment (2/30, 7%), primary outcome assessment (24/30, 80%), nonprimary outcome assessment (13/30, 43%), and extended follow-up (2/30, 7%). None of the studies used EHR for participant consent and randomization.

Conclusions
Despite the enormous potential of EHRs to increase the effectiveness and efficiency of conducting clinical trials in LMICs, challenges remain. Continued exploration of the appropriate uses of EHRs by navigating their strengths and limitations to ensure fitness for use is necessary to better understand the most optimal uses of EHRs for conducting clinical trials in LMICs.
A Device for Prehabilitation of Total Knee Replacement Surgery (Slider): Usability Study
Authors: Islam Riasat , Gooch Daniel , Karlakki Sudheer , Price Blaine 
Published: November 2023

Background
Rehabilitation, or “prehabilitation,” is essential in preparing for and recovering from knee replacement surgery. The recent demand for these services has surpassed available resources, a situation further strained by the COVID-19 pandemic, which has led to a pivot toward digital solutions such as web- or app-based videos and wearables. These solutions, however, face challenges with user engagement, calibration requirements, and skin contact issues. This study evaluated the practicality of a low-contact, gamified device designed to assist with prehabilitation exercises.

Objective
The study aimed to assess the practicality and user-friendliness of a newly designed physiotherapy device (Slider) that enables exercise monitoring without the need for direct contact with the skin.

Methods
A total of 17 patients awaiting knee replacement surgery at a UK National Health Service (NHS) hospital participated in this study. They used the device over a 2-week period and subsequently provided feedback through a usability and acceptability questionnaire.

Results
The study was completed by all participants, with a majority (13/17, 76%) finding the device intuitive and easy to use. The majority of patients were satisfied with the device’s ability to meet their presurgery physiotherapy requirements (16/17, 94%) and expressed a willingness to continue using it (17/17, 100%). No safety issues or adverse effects were reported by the participants.

Conclusions
The results indicate that the device was found to be a feasible option for patients to conduct presurgery physiotherapy exercises independently, away from a clinical setting. Further research involving a larger and more diverse group of participants is recommended to validate these findings more robustly.
Structural Validation and Measurement Invariance Testing of the Chinese Version of the eHealth Literacy Scale Among Undergraduates: Cross-Sectional Study
Authors: Long Chen , Zheng Lin , Liu Runhua , Duan Zhongxian 
Published: November 2023

Background
The eHealth Literacy Scale (eHEALS) was introduced in China in 2013 as one of the most important electronic health literacy measurement instruments. After a decade of development in China, it has received widespread attention, although its theoretical underpinnings have been challenged, thus demanding more robust research evidence of factorial validity and multigroup measurement properties.

Objective
This study aimed to evaluate the Chinese version of the eHEALS in terms of its measurement properties.

Methods
A cross-sectional survey was conducted in a university setting in China. Item statistics were checked for response distributions and floor and ceiling effects. Internal consistency reliability was confirmed with Cronbach α, split-half reliability, Cronbach α if an item was deleted, and item-total correlation. A total of 5 representative eHEALS factor structures were examined and contrasted using confirmatory factor analysis. The study used the item-level content validity index (I-CVI) and the average of the I-CVI scores of all items on the scale to assess the content validity of the dominance model. Furthermore, the validated dominance model was subsequently used to evaluate the relevance and representation of elements in the instrument and to assess measurement invariance across genders.

Results
A total of 972 respondents were identified, with a Cronbach α of .92, split-half reliability of 0.88, and item-total score correlation coefficients ranging from 0.715 to 0.781. Cronbach α if an item was deleted showed that all items should be retained. Acceptable content validity was supported by I-CVIs ≥0.80. The confirmatory factor analysis confirmed that the 3-factor model was acceptable. The measurement model met all relevant fit indices: average variance extracted from 0.663 to 0.680, composite reliability from 0.810 to 0.857, chi-square divided by the df of 4.768, root mean square error of approximation of 0.062, standardized root mean squared residual of 0.020, comparative fit index (CFI) of 0.987, and Tucker-Lewis index of 0.979. In addition, the scale demonstrated error variance invariance (Δnormed fit index=−0.016, Δincremental fit index=−0.012, ΔTucker-Lewis index=0.005, Δcomparative fit index=−0.012, Δrelative fit index=0.005, and Δroot mean square error of approximation=0.005).

Conclusions
A 3-factor model of the Chinese version of the eHEALS fits best, and our findings provide evidence for the strict measurement invariance of the instrument regarding gender.
Acceptance of a Web-Based Intervention in Individuals Who Committed Sexual Offenses Against Children: Cross-Sectional Study
Authors: Schröder Sonja , Buntrock Claudia , Neumann Louisa , Müller Jürgen L , Fromberger Peter 
Published: November 2023

Background
Individuals who have committed sexual offenses against children often have difficulties finding treatment, despite its potential effectiveness. Although the development of web-based interventions could enhance therapeutic supply, up to now the acceptance thereof among this target group is unknown.

Objective
For the first time, this study assesses the acceptance of a web-based intervention among individuals who committed sexual offenses against children and analyzes variables that predict acceptance. Following the Unified Theory of Acceptance and Use of Technology (UTAUT), it is assumed that acceptance of web-based interventions in individuals who have committed sexual offenses against children follows the same mechanisms as for individuals in general psychiatry.

Methods
This cross-sectional study is based on the data from an ongoing clinical trial (@myTabu) evaluating the effectiveness of a web-based intervention in individuals who committed sexual offenses against children (N=113). Acceptance level was measured using a questionnaire based on the UTAUT and modified for the target group. Furthermore, predictors of acceptance from the UTAUT (performance expectancy, effort expectancy, and social influence [SI]), attitudes toward web-based interventions, and internet anxiety were assessed at baseline.

Results
Most participants (61.1%, 69/113), reported high acceptance, while 36.3% (41/113) of them indicated moderate acceptance, and 2.7% (3/113) of them expressed low acceptance. In a linear regression model, the predictors explained 41.2% of the variance (F11,101=9.055; P=.01). Attitudes toward web-based interventions (B=0.398, 95% CI 0.16-0.64; P=.001) and SI (B=0.183, 95% CI 0.03-0.38; P=.04) significantly predicted acceptance. Post hoc explorative analysis showed that the participants’ belief that people close to them would recommend the use of a web-based intervention is a predictor of acceptance. In contrast, the belief that their community supervisor would recommend the use thereof was not predictive in this respect.

Conclusions
For the participants of this study, we identified high acceptance of web-based interventions for the majority of participants. SI and the participants’ attitudes toward web-based interventions were important in predicting acceptance.

Trial Registration
German Clinical Trial Registration (DRKS, Deutsches Register Klinischer Studien) DRKS 00021256; https://drks.de/search/de/trial/DRKS00021256
Toward an Interdisciplinary Approach to Constructing Care Delivery Pathways From Electronic Health Care Databases to Support Integrated Care in Chronic Conditions: Systematic Review of Quantification and Visualization Methods
Authors: Siqueira do Prado Luiza , Allemann Samuel , Viprey Marie , Schott Anne-Marie , Dediu Dan , Dima Alexandra Lelia 
Published: November 2023

Background
Electronic health care databases are increasingly used for informing clinical decision-making. In long-term care, linking and accessing information on health care delivered by different providers could improve coordination and health outcomes. Several methods for quantifying and visualizing this information into data-driven care delivery pathways (CDPs) have been proposed. To be integrated effectively and sustainably into routine care, these methods need to meet a range of prerequisites covering 3 broad domains: clinical, technological, and behavioral. Although advances have been made, development to date lacks a comprehensive interdisciplinary approach. As the field expands, it would benefit from developing common standards of development and reporting that integrate clinical, technological, and behavioral aspects.

Objective
We aimed to describe the content and development of long-term CDP quantification and visualization methods and to propose recommendations for future work.

Methods
We conducted a systematic review following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) recommendations. We searched peer-reviewed publications in English and reported the CDP methods by using the following data in the included studies: long-term care data and extracted data on clinical information and aims, technological development and characteristics, and user behaviors. The data are summarized in tables and presented narratively.

Results
Of the 2921 records identified, 14 studies were included, of which 13 (93%) were descriptive reports and 1 (7%) was a validation study. Clinical aims focused primarily on treatment decision-making (n=6, 43%) and care coordination (n=7, 50%). Technological development followed a similar process from scope definition to tool validation, with various levels of detail in reporting. User behaviors (n=3, 21%) referred to accessing CDPs, planning care, adjusting treatment, or supporting adherence.

Conclusions
The use of electronic health care databases for quantifying and visualizing CDPs in long-term care is an emerging field. Detailed and standardized reporting of clinical and technological aspects is needed. Early consideration of how CDPs would be used, validated, and implemented in clinical practice would likely facilitate further development and adoption.

Trial Registration
PROSPERO CRD42019140494; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=140494

International Registered Report Identifier (IRRID)
RR2-10.1136/bmjopen-2019-033573
An Exploration of the Goodness of Fit of Web-Based Tools for Māori: Qualitative Study Using Interviews and Focus Groups
Authors: Donkin Liesje , Bidois-Putt Marie-Claire , Wilson Holly , Hayward Penelope , Chan Amy Hai Yan 
Published: November 2023

Background
Indigenous communities often have poorer health outcomes and services under traditional models of care. In New Zealand, this holds true for Māori people who are tāngata whenua (the indigenous people). Several barriers exist that decrease the likelihood of indigenous communities often have poorer health outcomes and poor service fit under traditional models of care, including access issues, systemic and provider racism, and a lack of culturally safe and responsive services. Web-based interventions (WBIs) have been shown to be effective in supporting mental health and well-being and can overcome some of these barriers. Despite the large number of WBIs developed, more investigation is needed to know how well WBIs fit with an indigenous worldview and how they meet the needs of indigenous communities so that a digitally based future does not drive social and health inequities.

Objective
This study aims to explore the goodness-of-fit of WBIs of Māori individuals, the indigenous people of Aotearoa/New Zealand.

Methods
We used interviews (n=3) and focus groups (n=5) with 30 Māori participants to explore their views about WBIs. Interviews were analyzed using reflexive thematic analysis by members of the research team.

Results
Overall, there was a perception that the design of WBIs did not align with the Māori worldview, which centers around people, relationships, spirituality, and holistic views of well-being. A total of 4 key themes and several subthemes emerged, indicating that WBIs were generally considered a poor fit for Māori. Specifically, the themes were as follows: (1) WBIs are disconnected from the core values of te ao Māori (the Māori worldview), (2) WBIs could be helpful in the right context, (3) there are significant barriers that may make it harder for Māori to use WBIs than other groups, and (4) ways to improve WBIs to help engagement with Māori.

Conclusions
While WBIs are often considered a way to reduce barriers to care, they may not meet the needs of Māori when used as a stand-alone intervention. If WBIs are continued to be offered, developers and researchers need to consider how to develop WBIs that are responsive and engaging to the needs of indigenous communities rather than driving inequities. Ideally, WBIs should be developed by the people they are intended for to fit with those populations’ world views.
College Students’ Employability, Cognition, and Demands for ChatGPT in the AI Era Among Chinese Nursing Students: Web-Based Survey
Authors: Luo Yuanyuan , Weng Huiting , Yang Li , Ding Ziwei , Wang Qin 
Published: November 2023

Background
With the rapid development of artificial intelligence (AI) and the widespread use of ChatGPT, nursing students’ artificial intelligence quotient (AIQ), employability, cognition, and demand for ChatGPT are worthy of attention.

Objective
We aimed to investigate Chinese nursing students’ AIQ and employability status as well as their cognition and demand for the latest AI tool—ChatGPT. This study was conducted to guide future initiatives in nursing intelligence education and to improve the employability of nursing students.

Methods
We used a cross-sectional survey to understand nursing college students’ AIQ, employability, cognition, and demand for ChatGPT. Using correlation analysis and multiple hierarchical regression analysis, we explored the relevant factors in the employability of nursing college students.

Results
In this study, out of 1788 students, 1453 (81.30%) had not used ChatGPT, and 1170 (65.40%) had never heard of ChatGPT before this survey. College students’ employability scores were positively correlated with AIQ, self-regulation ability, and their home location and negatively correlated with school level. Additionally, men scored higher on college students’ employability compared to women. Furthermore, 76.5% of the variance was explained by the multiple hierarchical regression model for predicting college students’ employability scores.

Conclusions
Chinese nursing students have limited familiarity and experience with ChatGPT, while their AIQ remains intermediate. Thus, educators should pay more attention to cultivating nursing students’ AIQ and self-regulation ability to enhance their employability. Employability, especially for female students, those from rural backgrounds, and students in key colleges, deserves more attention in future educational efforts.