bluuebunny/crossref_metadata_2025_split huggingface dataset:
How Explainable Artificial Intelligence Can Increase or Decrease Clinicians’ Trust in AI Applications in Health Care: Systematic Review
Authors: Rosenbacke Rikard , Melhus Åsa , McKee Martin , Stuckler David 
Published: October 2024

Background
Artificial intelligence (AI) has significant potential in clinical practice. However, its “black box” nature can lead clinicians to question its value. The challenge is to create sufficient trust for clinicians to feel comfortable using AI, but not so much that they defer to it even when it produces results that conflict with their clinical judgment in ways that lead to incorrect decisions. Explainable AI (XAI) aims to address this by providing explanations of how AI algorithms reach their conclusions. However, it remains unclear whether such explanations foster an appropriate degree of trust to ensure the optimal use of AI in clinical practice.

Objective
This study aims to systematically review and synthesize empirical evidence on the impact of XAI on clinicians’ trust in AI-driven clinical decision-making.

Methods
A systematic review was conducted in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, searching PubMed and Web of Science databases. Studies were included if they empirically measured the impact of XAI on clinicians’ trust using cognition- or affect-based measures. Out of 778 articles screened, 10 met the inclusion criteria. We assessed the risk of bias using standard tools appropriate to the methodology of each paper.

Results
The risk of bias in all papers was moderate or moderate to high. All included studies operationalized trust primarily through cognitive-based definitions, with 2 also incorporating affect-based measures. Out of these, 5 studies reported that XAI increased clinicians’ trust compared with standard AI, particularly when the explanations were clear, concise, and relevant to clinical practice. In addition, 3 studies found no significant effect of XAI on trust, and the presence of explanations does not automatically improve trust. Notably, 2 studies highlighted that XAI could either enhance or diminish trust, depending on the complexity and coherence of the provided explanations. The majority of studies suggest that XAI has the potential to enhance clinicians’ trust in recommendations generated by AI. However, complex or contradictory explanations can undermine this trust. More critically, trust in AI is not inherently beneficial, as AI recommendations are not infallible. These findings underscore the nuanced role of explanation quality and suggest that trust can be modulated through the careful design of XAI systems.

Conclusions
Excessive trust in incorrect advice generated by AI can adversely impact clinical accuracy, just as can happen when correct advice is distrusted. Future research should focus on refining both cognitive and affect-based measures of trust and on developing strategies to achieve an appropriate balance in terms of trust, preventing both blind trust and undue skepticism. Optimizing trust in AI systems is essential for their effective integration into clinical practice.
Effect of Multimodal App-Based Interventions on Glycemic Control in Patients With Type 2 Diabetes: Systematic Review and Meta-Analysis
Authors: Bodner Emma , Roth Lena , Wiencke Kathleen , Bischoff Christian , Schwarz Peter EH 
Published: October 2024

Background
Digital technologies for type 2 diabetes mellitus (T2DM) care hold great potential to improve patients’ health in the long term. Only a subset of telemedicine offerings are digital interventions that meet the criteria for prescribable digitale Gesundheitsanwendung (digital health apps; DiGAs) in Germany. Digital treatments further provide vast amounts of patient data that are important to generate evidence.

Objective
This systematic review aims to analyze the efficacy of multimodal digital therapies that mainly meet the DiGA criteria for patients with T2DM and to elicit the potential of such therapies. This includes evidence from randomized controlled trials (RCTs) as well as from real-world data. The outcome of interest was a reduction in glycated hemoglobin (hemoglobin A1c [HbA1c]; long-term blood glucose measurements).

Methods
A systematic literature search was conducted in the literature bases PubMed, LIVIVO, and Cochrane, based on the predefined PICO (Population; Intervention; Control; Outcome) scheme. Identified studies were assessed for risk of bias, pragmatism, and overall quality of evidence. Meta-analyses were conducted for between group differences using RCTs only, and for within-group differences using RCTs and non-RCTs, to examine the effect of the interventions on HbA1c.

Results
In total, 795 records were identified, of which 24 were eligible for this systematic review and 23 studies were eligible for the meta-analysis. The results of the meta-analyses showed significant and clinically relevant reductions in HbA1c in patients with T2DM. Regarding the between-group difference for HbA1c reduction, the pooled effect of the RCTs showed a reduction of –0.36% (95% CI –0.59% to –0.14%; P<.001), favoring app-based interventions. The average mean within-group reduction in HbA1c was –0.79 (95% CI –1.02 to –0.55), with no significant difference between RCTs (–0.69, 95% CI –1.13 to –0.24) and non-RCTs (–0.87, 95% CI –1.16 to –0.57; P<.01, differences between RCTs and RCTs P=.44). A pragmatism rating showed that both study types were on average (very) pragmatic, that is, close to usual care. However, the overall quality of evidence was low to very low.

Conclusions
This systematic review shows that digital therapies that mainly meet the DiGA criteria can effectively improve HbA1c in patients with T2DM. The integration of digital health care into usual care holds great potential and should be considered as a complementary option to usual care in the future.

Trial Registration
PROSPERO CRD42023440203; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=440203
Evaluating the Implementation and Clinical Effectiveness of an Innovative Digital First Care Model for Behavioral Health Using the RE-AIM Framework: Quantitative Evaluation
Authors: Nordberg Samuel S , Jaso-Yim Brittany A , Sah Pratha , Schuler Keke , Eyllon Mara , Pennine Mariesa , Hoyler Georgia H , Barnes J Ben , Murillo Lily Hong , O'Dea Heather , Orth Laura , Rogers Elizabeth , Welch George , Peloquin Gabrielle , Youn Soo Jeong 
Published: October 2024

Background
In the United States, innovation is needed to address the increasing need for mental health care services and widen the patient-to-provider ratio. Despite the benefits of digital mental health interventions (DMHIs), they have not been effective in addressing patients’ behavioral health challenges as stand-alone treatments.

Objective
This study evaluates the implementation and effectiveness of precision behavioral health (PBH), a digital-first behavioral health care model embedded within routine primary care that refers patients to an ecosystem of evidence-based DMHIs with strategically placed human support.

Methods
Patient demographic information, triage visit outcomes, multidimensional patient-reported outcome measure, enrollment, and engagement with the DMHIs were analyzed using data from the electronic health record and vendor-reported data files. The RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) framework was used to evaluate the implementation and clinical effectiveness outcomes of PBH.

Results
PBH had a 47.58% reach rate, defined as patients accepting the PBH referral from their behavioral health integrated clinician. PBH patients had high DMHI registration rates (79.62%), high activation rates (76.54%), and high retention rates at 15 days (57.69%) and 30 days (44.58%) compared to literature benchmarks. In total, 74.01% (n=168) of patients showed clinical improvement, 22.47% (n=51) showed no clinical change, and 3.52% (n=8) showed clinical deterioration in symptoms. PBH had high adoption rates, with behavioral health integrated clinicians referring on average 4.35 (SD 0.46) patients to PBH per month and 90%-100% of clinicians (n=12) consistently referring at least 1 patient to PBH each month. A third (32%, n=1114) of patients were offered PBH as a treatment option during their triage visit.

Conclusions
PBH as a care model with evidence-based DMHIs, human support for patients, and integration within routine settings offers a credible service to support patients with mild to moderate mental health challenges. This type of model has the potential to address real-life access to care problems faced by health care settings.
The Implementation of the Advocacy Intervention for Midlife and Older Women Who Have Experienced Intimate Partner Violence: Protocol for a Randomized Controlled Trial
Authors: Weeks Lori , Allen Kathleen , Holtmann Catherine , Leger Joni , Dupuis-Blanchard Suzanne , MacQuarrie Colleen , Macdonald Marilyn , Moody Elaine , Stilwell Christie , Helpard Heather , Gagnon Danie 
Published: October 2024

Background
Midlife and older women who experience intimate partner violence (IPV) often have less access to supports and services than younger women. There is far less focus on research and supports for midlife and older women compared to younger women experiencing IPV, and often, neither elder abuse nor IPV services meet their needs. Few interventions are available to meet the needs of midlife and older women.

Objective
The goal of this randomized controlled trial is to test the effectiveness of an advocacy intervention for midlife and older women who experience IPV and to learn from the experiences of those who implement and participate in the program.

Methods
This trial is a 2-arm, unblinded, parallel, pragmatic randomized controlled trial with a qualitative component. Eligible participants will be women who live in the Maritime provinces of Canada (New Brunswick, Nova Scotia, and Prince Edward Island), who are in midlife and older (aged approximately ≥50 years), and who are currently in a relationship with an abusive partner or have recently left an abusive partner. Facilitators will be trained to deliver the intervention. The intervention will be entirely virtual and will consist of 2 components: (1) an empowerment component, which will involve sharing resources and information with the women; and (2) a social support component, which will include providing support and encouragement to women for 12 weeks. Quantitative effectiveness data will be collected from all trial participants at baseline, 3 months after the intervention, and 9 months after the intervention about the incidence and severity of IPV, physical and mental health, and safety behaviors and strategies. Qualitative interviews will be conducted with the facilitators and intervention group participants. Control group participants will receive a static, nontailored version of the advocacy intervention for midlife and older women (AIM) intervention materials after baseline data collection.

Results
A total of 12 facilitators have been trained to deliver the AIM intervention to trial participants. Participant recruitment and data collection will be completed in January 2025. Data analysis will continue throughout the data collection period, and the results will be disseminated by December 2025.

Conclusions
This research will result in the adaptation and testing of a program to support and empower midlife and older women in the Maritime provinces of Canada who experience IPV.

Trial Registration
International Standard Randomized Controlled Trial Registry ISRCTN30646991; https://doi.org/10.1186/ISRCTN30646991

International Registered Report Identifier (IRRID)
DERR1-10.2196/57886
Ensuring Accuracy and Equity in Vaccination Information From ChatGPT and CDC: Mixed-Methods Cross-Language Evaluation
Authors: Joshi Saubhagya , Ha Eunbin , Amaya Andee , Mendoza Melissa , Rivera Yonaira , Singh Vivek K 
Published: October 2024

Background
In the digital age, large language models (LLMs) like ChatGPT have emerged as important sources of health care information. Their interactive capabilities offer promise for enhancing health access, particularly for groups facing traditional barriers such as insurance and language constraints. Despite their growing public health use, with millions of medical queries processed weekly, the quality of LLM-provided information remains inconsistent. Previous studies have predominantly assessed ChatGPT’s English responses, overlooking the needs of non–English speakers in the United States. This study addresses this gap by evaluating the quality and linguistic parity of vaccination information from ChatGPT and the Centers for Disease Control and Prevention (CDC), emphasizing health equity.

Objective
This study aims to assess the quality and language equity of vaccination information provided by ChatGPT and the CDC in English and Spanish. It highlights the critical need for cross-language evaluation to ensure equitable health information access for all linguistic groups.

Methods
We conducted a comparative analysis of ChatGPT’s and CDC’s responses to frequently asked vaccination-related questions in both languages. The evaluation encompassed quantitative and qualitative assessments of accuracy, readability, and understandability. Accuracy was gauged by the perceived level of misinformation; readability, by the Flesch-Kincaid grade level and readability score; and understandability, by items from the National Institutes of Health’s Patient Education Materials Assessment Tool (PEMAT) instrument.

Results
The study found that both ChatGPT and CDC provided mostly accurate and understandable (eg, scores over 95 out of 100) responses. However, Flesch-Kincaid grade levels often exceeded the American Medical Association’s recommended levels, particularly in English (eg, average grade level in English for ChatGPT=12.84, Spanish=7.93, recommended=6). CDC responses outperformed ChatGPT in readability across both languages. Notably, some Spanish responses appeared to be direct translations from English, leading to unnatural phrasing. The findings underscore the potential and challenges of using ChatGPT for health care access.

Conclusions
ChatGPT holds potential as a health information resource but requires improvements in readability and linguistic equity to be truly effective for diverse populations. Crucially, the default user experience with ChatGPT, typically encountered by those without advanced language and prompting skills, can significantly shape health perceptions. This is vital from a public health standpoint, as the majority of users will interact with LLMs in their most accessible form. Ensuring that default responses are accurate, understandable, and equitable is imperative for fostering informed health decisions across diverse communities.
Experiences of Older Mental Health Patients and Their Care Partners Using a Proxy Account to Access Open Notes: Qualitative Interview Study
Authors: Meier-Diedrich Eva , Esch Tobias , Hägglund Maria , Heinze Martin , Hochwarter Stefan , Speck Justin , Wagener Marie , Dahling Volker , Schwarz Julian 
Published: October 2024

Background
Older patients with serious mental illnesses such as cognitive disorders often rely on family members or spouses (care partners [CPs]) to meet their health care needs. CPs frequently lack essential information to fully understand the patients’ illnesses and effectively support their treatment. Open Notes provide patients with digital access to their health care professionals’ clinical notes and are associated with many positive outcomes, such as increased adherence and empowerment. However, older patients who use Open Notes may encounter use barriers such as limited digital literacy. Recent developments allow CPs to access Open Notes (proxy access) and receive valuable information, which holds significant potential for improving the care of older patients.

Objective
This study explored the experiences, barriers, and opportunities of older mental health patients and their CPs related to using Open Notes. Furthermore, influencing factors and interdependencies were identified.

Methods
Older patients (n=10) and their CPs (n=10) were provided with web-based proxy access to clinical documentation through a web-based patient portal. In-depth qualitative interviews (N=20) were conducted to explore experiences with this access. Data analysis was conducted in accordance with the constructivist grounded theory approach.

Results
The prerequisites for using Open Notes with proxy access were sufficient digital literacy on the part of the patient or CP, as well as the establishment of a trusting relationship between patients and CPs. Access to Open Notes enabled patients and CPs to gain a deeper understanding of the illness and its treatment while also facilitating enhanced contact with health care professionals. This resulted in greater involvement in the treatment process but may also prompt changes in relationship dynamics—CPs are better equipped to support patients in their health care but may also tend to monitor or control them through Open Notes. As a result, the introduction of Open Notes was accompanied by mixed feelings.

Conclusions
It is of utmost importance to provide older patients with comprehensive access to Open Notes to preserve their health autonomy. However, the involvement of CPs through proxy access is of great value in improving the care of older patients, especially those with cognitive impairments.
The analysis of partial consent implementation effectiveness for terms & conditions on data awareness and data security of social media application users
Authors: Kurniawan Yohannes , Tsany Mufid Hilmy , Kamil Mufti Ikhsan , Alif Nabil , Anwar Norizan 
Published: October 2024

Terms and Conditions are always encountered when using social media applications to determine which data can be accessed and what cannot. However, there are shortcomings in their implementation and communication, often causing users to be unwilling to read them. Therefore, this study aimed to analyze the effectiveness of implementing partial consent in Terms and Conditions concerning user Data Awareness and Data Security in social media. This Paper administered a questionnaire, distributed with a form, to students who use social media to understand their opinions regarding the partial consent concept. This paper analyzed the data using descriptive statistical methods. The results show a positive response from respondents towards implementing the partial consent concept, the users feel the terms and conditions are more effective in increasing user data awareness and security.
An empirical study of interactive experience and teaching effect of erhu performance in virtual reality environment
Authors: Wang Luying 
Published: October 2024

Abstract
In today’s extremely rich material civilization, it is necessary to take the initiative to combine the inheritance of the erhu art with modern means, and in this regard, an immersive virtual erhu playing experience multi-channel interactive system is proposed. The multi-channel interactive system for an immersive virtual erhu playing experience is constructed by combining knowledge of erhu playing. The multi-channel interaction function module of this system consists of acoustic feedback, haptic perception, gesture recognition, and line-of-sight tracking interaction, while the virtual playing module contains two parts: dynamic guidance teaching and navigation menu distribution. Based on the research purpose, the system function and teaching effect are verified and analyzed. The results indicate that the system can recognize simple erhu-playing gestures with a recognition rate of 100.00% and can recognize relatively complex gestures with a recognition rate of more than 95.00%, thereby providing users with an enjoyable erhu-playing experience. The three aspects of erhu playing knowledge, rhythm ability, and improvisation ability show a significant difference between the traditional erhu teaching method and the system presented in this paper, with a P-value of less than 0.05. This difference clearly demonstrates the promotion effect of the interactive system on erhu performance teaching.
A Cluster Analysis Study on the Relevance of Innovation Design and Development Influencing Factors in Dehua Ceramics Industry
Authors: Zhao Peng , Shen Lu 
Published: October 2024

Abstract
The emergence of technological innovation in Dehua ceramics has brought new impetus to the spread of ceramic culture. By mining the market characteristics of ceramic technology innovation, we analyze the influencing factors of Dehua’s ceramic innovation development. Based on big data technology, this paper collects data related to the development of the Dehua ceramics industry, and after pre-processing the data, a classical division-based K-means clustering algorithm is used to make a division and explore the innovation characteristics of different Dehua ceramics industries. On this basis, correlation analysis and regression analysis were introduced to explore the influencing factors of innovative design and development in the Dehua ceramic industry. The second and third clusters in the purchase of innovatively designed Dehua ceramics accounted for 100% and 91%, respectively. It shows that the market demand for innovative design in Dehua Ceramics is large. The company type factor is the most critical influence factor for the development of innovative design in Dehua Ceramic Company, which can be changed by changing the type of company to promote the development of innovative design in the industry. The clustering result analysis in this paper accurately reflects the market characteristics of Dehua Ceramics, and the regression analysis accurately reflects the influence factors related to the development of innovative designs in the Dehua Ceramics industry.
The impact of multichannel integration of service quality and customer experience on repurchase intention based on data mining
Authors: Liu Enxi 
Published: October 2024

Abstract
Under the dual factors of the rapid development of network technology and the transformation of consumer behavior, major enterprises have sought innovation and transformation, but most of them do not have a clear idea of effective multi-channel integration. This paper collects the browsing records of new users on the Tmall platform in 2023 as sample data for empirical analysis. The data visualization and analysis of the repurchase rates of different stores, genders, and ages reveal that the repurchase rates of different stores, genders, and ages are different. As far as different genders are concerned, the repurchase rate of women is higher than that of men, and its probability distribution is between 0.06 and 0.1. Based on the S-O-R theory, combined with the multiple regression analysis method, it is found that service quality and customer experience play a positive influence on customers’ repurchase, and for every 1 unit improvement in service quality and customer experience, customers’ repurchase willingness will increase by 0.124 and 0.257 respectively. Perceived value has a moderating effect on service quality and customer experience during the process of influencing customers’ willingness to repurchase. For example, for every 1 unit increase in hedonic value and service quality, hedonic value, and customer experience, the repurchase willingness of customers increases by 0.423 and 0.416, respectively. The research in this paper provides effective technical support for enterprises, stores, and platforms to formulate precise marketing plans, reduce costs, and increase efficiency.