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Abstract Background The GRADE-CERQual (Confidence in Evidence from Reviews of Qualitative research) approach has been developed by the GRADE (Grading of Recommendations Assessment, Development and Evaluation) Working Group. The approach has been developed to support the use of findings from qualitative evidence syntheses in decision-making, including guideline development and policy formulation. CERQual includes four components for assessing how much confidence to place in findings from reviews of qualitative research (also referred to as qualitative evidence syntheses): (1) methodological limitations, (2) coherence, (3) adequacy of data and (4) relevance. This paper is part of a series providing guidance on how to apply CERQual and focuses on CERQual’s relevance component. Methods We developed the relevance component by searching the literature for definitions, gathering feedback from relevant research communities and developing consensus through project group meetings. We tested the CERQual relevance component within several qualitative evidence syntheses before agreeing on the current definition and principles for application. Results When applying CERQual, we define relevance as the extent to which the body of data from the primary studies supporting a review finding is applicable to the context (perspective or population, phenomenon of interest, setting) specified in the review question. In this paper, we describe the relevance component and its rationale and offer guidance on how to assess relevance in the context of a review finding. This guidance outlines the information required to assess relevance, the steps that need to be taken to assess relevance and examples of relevance assessments. Conclusions This paper provides guidance for review authors and others on undertaking an assessment of relevance in the context of the CERQual approach. Assessing the relevance component requires consideration of potentially important contextual factors at an early stage in the review process. We expect the CERQual approach, and its individual components, to develop further as our experiences with the practical implementation of the approach increase.

Abstract Background The GRADE-CERQual (Confidence in Evidence from Reviews of Qualitative research) approach has been developed by the GRADE (Grading of Recommendations Assessment, Development and Evaluation) Working Group. The approach has been developed to support the use of findings from qualitative evidence syntheses in decision-making, including guideline development and policy formulation. CERQual includes four components for assessing how much confidence to place in findings from reviews of qualitative research (also referred to as qualitative evidence syntheses): (1) methodological limitations, (2) coherence, (3) adequacy of data and (4) relevance. This paper is part of a series providing guidance on how to apply CERQual and focuses on a probable fifth component, dissemination bias. Given its exploratory nature, we are not yet able to provide guidance on applying this potential component of the CERQual approach. Instead, we focus on how dissemination bias might be conceptualised in the context of qualitative research and the potential impact dissemination bias might have on an overall assessment of confidence in a review finding. We also set out a proposed research agenda in this area. Methods We developed this paper by gathering feedback from relevant research communities, searching MEDLINE and Web of Science to identify and characterise the existing literature discussing or assessing dissemination bias in qualitative research and its wider implications, developing consensus through project group meetings, and conducting an online survey of the extent, awareness and perceptions of dissemination bias in qualitative research. Results We have defined dissemination bias in qualitative research as a systematic distortion of the phenomenon of interest due to selective dissemination of studies or individual study findings. Dissemination bias is important for qualitative evidence syntheses as the selective dissemination of qualitative studies and/or study findings may distort our understanding of the phenomena that these syntheses aim to explore and thereby undermine our confidence in these findings. Dissemination bias has been extensively examined in the context of randomised controlled trials and systematic reviews of such studies. The effects of potential dissemination bias are formally considered, as publication bias, within the GRADE approach. However, the issue has received almost no attention in the context of qualitative research. Because of very limited understanding of dissemination bias and its potential impact on review findings in the context of qualitative evidence syntheses, this component is currently not included in the GRADE-CERQual approach. Conclusions Further research is needed to establish the extent and impacts of dissemination bias in qualitative research and the extent to which dissemination bias needs to be taken into account when we assess how much confidence we have in findings from qualitative evidence syntheses.

Abstract Background The GRADE-CERQual (Grading of Recommendations Assessment, Development and Evaluation-Confidence in Evidence from Reviews of Qualitative research) approach has been developed by the GRADE working group. The approach has been developed to support the use of findings from qualitative evidence syntheses in decision-making, including guideline development and policy formulation. CERQual includes four components for assessing how much confidence to place in findings from reviews of qualitative research (also referred to as qualitative evidence syntheses): (1) methodological limitations, (2) relevance, (3) coherence and (4) adequacy of data. This paper is part of a series providing guidance on how to apply CERQual and focuses on CERQual’s coherence component. Methods We developed the coherence component by searching the literature for definitions, gathering feedback from relevant research communities and developing consensus through project group meetings. We tested the CERQual coherence component within several qualitative evidence syntheses before agreeing on the current definition and principles for application. Results When applying CERQual, we define coherence as how clear and cogent the fit is between the data from the primary studies and a review finding that synthesises that data. In this paper, we describe the coherence component and its rationale and offer guidance on how to assess coherence in the context of a review finding as part of the CERQual approach. This guidance outlines the information required to assess coherence, the steps that need to be taken to assess coherence and examples of coherence assessments. Conclusions This paper provides guidance for review authors and others on undertaking an assessment of coherence in the context of the CERQual approach. We suggest that threats to coherence may arise when the data supporting a review finding are contradictory, ambiguous or incomplete or where competing theories exist that could be used to synthesise the data. We expect the CERQual approach, and its individual components, to develop further as our experiences with the practical implementation of the approach increase.

Abstract Background The GRADE-CERQual (Confidence in Evidence from Reviews of Qualitative research) approach has been developed by the GRADE (Grading of Recommendations Assessment, Development and Evaluation) Working Group. The approach has been developed to support the use of findings from qualitative evidence syntheses in decision making, including guideline development and policy formulation. CERQual includes four components for assessing how much confidence to place in findings from reviews of qualitative research (also referred to as qualitative evidence syntheses): (1) methodological limitations, (2) coherence, (3) adequacy of data and (4) relevance. This paper is part of a series providing guidance on how to apply CERQual and focuses on making an overall assessment of confidence in a review finding and creating a CERQual Evidence Profile and a CERQual Summary of Qualitative Findings table. Methods We developed this guidance by examining the methods used by other GRADE approaches, gathering feedback from relevant research communities and developing consensus through project group meetings. We then piloted the guidance on several qualitative evidence syntheses before agreeing on the approach. Results Confidence in the evidence is an assessment of the extent to which a review finding is a reasonable representation of the phenomenon of interest. Creating a summary of each review finding and deciding whether or not CERQual should be used are important steps prior to assessing confidence. Confidence should be assessed for each review finding individually, based on the judgements made for each of the four CERQual components. Four levels are used to describe the overall assessment of confidence: high, moderate, low or very low. The overall CERQual assessment for each review finding should be explained in a CERQual Evidence Profile and Summary of Qualitative Findings table. Conclusions Structuring and summarising review findings, assessing confidence in those findings using CERQual and creating a CERQual Evidence Profile and Summary of Qualitative Findings table should be essential components of undertaking qualitative evidence syntheses. This paper describes the end point of a CERQual assessment and should be read in conjunction with the other papers in the series that provide information on assessing individual CERQual components.

Abstract Background The GRADE-CERQual (Confidence in Evidence from Reviews of Qualitative research) approach has been developed by the GRADE (Grading of Recommendations Assessment, Development and Evaluation) Working Group. The approach has been developed to support the use of findings from qualitative evidence syntheses in decision-making, including guideline development and policy formulation. CERQual includes four components for assessing how much confidence to place in findings from reviews of qualitative research (also referred to as qualitative evidence syntheses): (1) methodological limitations, (2) coherence, (3) adequacy of data and (4) relevance. This paper is part of a series providing guidance on how to apply CERQual and focuses on CERQual’s methodological limitations component. Methods We developed the methodological limitations component by searching the literature for definitions, gathering feedback from relevant research communities and developing consensus through project group meetings. We tested the CERQual methodological limitations component within several qualitative evidence syntheses before agreeing on the current definition and principles for application. Results When applying CERQual, we define methodological limitations as the extent to which there are concerns about the design or conduct of the primary studies that contributed evidence to an individual review finding. In this paper, we describe the methodological limitations component and its rationale and offer guidance on how to assess methodological limitations of a review finding as part of the CERQual approach. This guidance outlines the information required to assess methodological limitations component, the steps that need to be taken to assess methodological limitations of data contributing to a review finding and examples of methodological limitation assessments. Conclusions This paper provides guidance for review authors and others on undertaking an assessment of methodological limitations in the context of the CERQual approach. More work is needed to determine which criteria critical appraisal tools should include when assessing methodological limitations. We currently recommend that whichever tool is used, review authors provide a transparent description of their assessments of methodological limitations in a review finding. We expect the CERQual approach and its individual components to develop further as our experiences with the practical implementation of the approach increase.

Abstract Background The GRADE-CERQual (Confidence in Evidence from Reviews of Qualitative research) approach has been developed by the GRADE (Grading of Recommendations Assessment, Development and Evaluation) working group. The approach has been developed to support the use of findings from qualitative evidence syntheses in decision-making, including guideline development and policy formulation. CERQual includes four components for assessing how much confidence to place in findings from reviews of qualitative research (also referred to as qualitative evidence syntheses): (1) methodological limitations; (2) coherence; (3) adequacy of data; and (4) relevance. This paper is part of a series providing guidance on how to apply CERQual and focuses on CERQual’s adequacy of data component. Methods We developed the adequacy of data component by searching the literature for definitions, gathering feedback from relevant research communities and developing consensus through project group meetings. We tested the CERQual adequacy of data component within several qualitative evidence syntheses before agreeing on the current definition and principles for application. Results When applying CERQual, we define adequacy of data as an overall determination of the degree of richness and the quantity of data supporting a review finding. In this paper, we describe the adequacy component and its rationale and offer guidance on how to assess data adequacy in the context of a review finding as part of the CERQual approach. This guidance outlines the information required to assess data adequacy, the steps that need to be taken to assess data adequacy, and examples of adequacy assessments. Conclusions This paper provides guidance for review authors and others on undertaking an assessment of adequacy in the context of the CERQual approach. We approach assessments of data adequacy in terms of the richness and quantity of the data supporting each review finding, but do not offer fixed rules regarding what constitutes sufficiently rich data or an adequate quantity of data. Instead, we recommend that this assessment is made in relation to the nature of the finding. We expect the CERQual approach, and its individual components, to develop further as our experiences with the practical implementation of the approach increase.

The article focuses on how online education enhances physiotherapists' confidence and competence in mechanical insufflation-exsufflation. Topics discussed include the effectiveness of online learning, its impact on healthcare professionals' skills development, and the role of technology in advancing medical education.

The article focuses on the impact of online education on enhancing physiotherapists' confidence and competence in mechanical insufflation-exsufflation. Topics discussed include the effectiveness of online learning platforms, their role in advancing healthcare professionals' skills, and their implications for respiratory care practices.

Most nursing simulation programs focus on persons' healthcare needs in hospital settings, and little is known about how to identify them in home settings. This study aims to develop and validate a virtual reality (VR) simulation program for nursing students to improve their clinical reasoning skills and confidence in assessing persons' healthcare needs in home settings. We developed a VR simulation program based on a literature review and expert discussion. In Phase 1, home visit nurses or public health nurses will validate the program through their interviews in 2022. In Phase 2, we will conduct a pilot and main single-blinded randomized trial for nursing students to confirm the effectiveness from 2022 and 2023. Participants will be randomly allocated into an intervention group using VR simulations and a control group receiving videos regarding three kinds of community residents' lives [1:1]. After obtaining informed consent, the students will submit their anonymous data to the researchers to prevent associating their grade evaluation. The primary outcome will be their clinical reasoning skills. The second outcome will include their satisfaction and self-confidence. This study will examine the effectiveness of improving their clinical reasoning skills and confidence in assessing persons' healthcare needs in home settings. [ABSTRACT FROM AUTHOR]

The article focuses on the application of participation-focused therapy in children with cerebral palsy for improvement in physical activity goal performance, satisfaction, and confidence.

Higher education institutions are uniquely placed to introduce emotional coping skills to promote resilience in pre-registration nurses in order to reduce anxiety and increase confidence before they enter clinical placement for the first time. In this qualitative study, we will explore the use of a 360-degree video in developing skills for coping. The participants will be mental health nursing students. We will develop a 360-degree video in collaboration with a mental health service user. All participants will watch the video. A sub-group will receive a supportive clinical supervision discussion within a cognitive reappraisal/solution-focused/VERA framework. We will record the experiences of the participant to explore: (1) how students felt about the use of 360-degree video, as an education tool to build skills of resilience; (2) whether the students involved felt more confident and less anxious about the situation in the video as a result of participating in the cognitive reappraisal/solution-focused/VERA supervision discussion. [ABSTRACT FROM AUTHOR]

Background: The GRADE-CERQual (Confidence in Evidence from Reviews of Qualitative research) approach has been developed by the GRADE (Grading of Recommendations Assessment, Development and Evaluation) Working Group. The approach has been developed to support the use of findings from qualitative evidence syntheses in decision-making, including guideline development and policy formulation. CERQual includes four components for assessing how much confidence to place in findings from reviews of qualitative research (also referred to as qualitative evidence syntheses): (1) methodological limitations, (2) coherence, (3) adequacy of data and (4) relevance. This paper is part of a series providing guidance on how to apply CERQual and focuses on CERQual's relevance component.Methods: We developed the relevance component by searching the literature for definitions, gathering feedback from relevant research communities and developing consensus through project group meetings. We tested the CERQual relevance component within several qualitative evidence syntheses before agreeing on the current definition and principles for application.Results: When applying CERQual, we define relevance as the extent to which the body of data from the primary studies supporting a review finding is applicable to the context (perspective or population, phenomenon of interest, setting) specified in the review question. In this paper, we describe the relevance component and its rationale and offer guidance on how to assess relevance in the context of a review finding. This guidance outlines the information required to assess relevance, the steps that need to be taken to assess relevance and examples of relevance assessments.Conclusions: This paper provides guidance for review authors and others on undertaking an assessment of relevance in the context of the CERQual approach. Assessing the relevance component requires consideration of potentially important contextual factors at an early stage in the review process. We expect the CERQual approach, and its individual components, to develop further as our experiences with the practical implementation of the approach increase. [ABSTRACT FROM AUTHOR]

Background: The GRADE-CERQual (Confidence in Evidence from Reviews of Qualitative research) approach has been developed by the GRADE (Grading of Recommendations Assessment, Development and Evaluation) working group. The approach has been developed to support the use of findings from qualitative evidence syntheses in decision-making, including guideline development and policy formulation. CERQual includes four components for assessing how much confidence to place in findings from reviews of qualitative research (also referred to as qualitative evidence syntheses): (1) methodological limitations; (2) coherence; (3) adequacy of data; and (4) relevance. This paper is part of a series providing guidance on how to apply CERQual and focuses on CERQual's adequacy of data component.Methods: We developed the adequacy of data component by searching the literature for definitions, gathering feedback from relevant research communities and developing consensus through project group meetings. We tested the CERQual adequacy of data component within several qualitative evidence syntheses before agreeing on the current definition and principles for application.Results: When applying CERQual, we define adequacy of data as an overall determination of the degree of richness and the quantity of data supporting a review finding. In this paper, we describe the adequacy component and its rationale and offer guidance on how to assess data adequacy in the context of a review finding as part of the CERQual approach. This guidance outlines the information required to assess data adequacy, the steps that need to be taken to assess data adequacy, and examples of adequacy assessments.Conclusions: This paper provides guidance for review authors and others on undertaking an assessment of adequacy in the context of the CERQual approach. We approach assessments of data adequacy in terms of the richness and quantity of the data supporting each review finding, but do not offer fixed rules regarding what constitutes sufficiently rich data or an adequate quantity of data. Instead, we recommend that this assessment is made in relation to the nature of the finding. We expect the CERQual approach, and its individual components, to develop further as our experiences with the practical implementation of the approach increase. [ABSTRACT FROM AUTHOR]

Background: The GRADE-CERQual (Grading of Recommendations Assessment, Development and Evaluation-Confidence in Evidence from Reviews of Qualitative research) approach has been developed by the GRADE working group. The approach has been developed to support the use of findings from qualitative evidence syntheses in decision-making, including guideline development and policy formulation. CERQual includes four components for assessing how much confidence to place in findings from reviews of qualitative research (also referred to as qualitative evidence syntheses): (1) methodological limitations, (2) relevance, (3) coherence and (4) adequacy of data. This paper is part of a series providing guidance on how to apply CERQual and focuses on CERQual's coherence component.Methods: We developed the coherence component by searching the literature for definitions, gathering feedback from relevant research communities and developing consensus through project group meetings. We tested the CERQual coherence component within several qualitative evidence syntheses before agreeing on the current definition and principles for application.Results: When applying CERQual, we define coherence as how clear and cogent the fit is between the data from the primary studies and a review finding that synthesises that data. In this paper, we describe the coherence component and its rationale and offer guidance on how to assess coherence in the context of a review finding as part of the CERQual approach. This guidance outlines the information required to assess coherence, the steps that need to be taken to assess coherence and examples of coherence assessments.Conclusions: This paper provides guidance for review authors and others on undertaking an assessment of coherence in the context of the CERQual approach. We suggest that threats to coherence may arise when the data supporting a review finding are contradictory, ambiguous or incomplete or where competing theories exist that could be used to synthesise the data. We expect the CERQual approach, and its individual components, to develop further as our experiences with the practical implementation of the approach increase. [ABSTRACT FROM AUTHOR]

Background: The GRADE-CERQual (Confidence in Evidence from Reviews of Qualitative research) approach has been developed by the GRADE (Grading of Recommendations Assessment, Development and Evaluation) Working Group. The approach has been developed to support the use of findings from qualitative evidence syntheses in decision-making, including guideline development and policy formulation. CERQual includes four components for assessing how much confidence to place in findings from reviews of qualitative research (also referred to as qualitative evidence syntheses): (1) methodological limitations, (2) coherence, (3) adequacy of data and (4) relevance. This paper is part of a series providing guidance on how to apply CERQual and focuses on CERQual's methodological limitations component.Methods: We developed the methodological limitations component by searching the literature for definitions, gathering feedback from relevant research communities and developing consensus through project group meetings. We tested the CERQual methodological limitations component within several qualitative evidence syntheses before agreeing on the current definition and principles for application.Results: When applying CERQual, we define methodological limitations as the extent to which there are concerns about the design or conduct of the primary studies that contributed evidence to an individual review finding. In this paper, we describe the methodological limitations component and its rationale and offer guidance on how to assess methodological limitations of a review finding as part of the CERQual approach. This guidance outlines the information required to assess methodological limitations component, the steps that need to be taken to assess methodological limitations of data contributing to a review finding and examples of methodological limitation assessments.Conclusions: This paper provides guidance for review authors and others on undertaking an assessment of methodological limitations in the context of the CERQual approach. More work is needed to determine which criteria critical appraisal tools should include when assessing methodological limitations. We currently recommend that whichever tool is used, review authors provide a transparent description of their assessments of methodological limitations in a review finding. We expect the CERQual approach and its individual components to develop further as our experiences with the practical implementation of the approach increase. [ABSTRACT FROM AUTHOR]

The paper reexamines an agent-based model of opinion formation under bounded confidence with heterogeneous agents. The paper is novel in that it extends the standard model of opinion dynamics with the assumption that interacting agents share the desire to exchange opinion. In particular, the interaction between agents in the paper is modeled via a dynamic preferential-matching process wherein agents reveal their preferences to meet according to three features: coherence, opinion difference, and agents' positive sentiments towards others. Only preferred matches meet and exchange opinion. Through an extensive series of simulation treatments, it follows that the presence of sentiments, on one hand, hardens the matching process between agents, which leads to less communication. But, on the other hand, it increases the diversity in preferred matches between agents and thereby leads to a better-integrated social network structure, which reflects in a reduction of the opinion variance between agents. Moreover, at combinations of (a) high tolerance, (b) low sensitivity of agents to opinion volatility, and (c) low levels of confidence, agents are occasionally drawn away from the consensus, forming small groups that hold extreme opinions. [ABSTRACT FROM AUTHOR]

Objective: To practice evidence-based medicine, clinicians must be competent in information literacy (IL). Few studies acknowledge the critical role that reading strategies play in IL instruction and assessment of health professional students. The purpose of this study was to understand the information-seeking and evaluation behaviors of doctor of veterinary medicine (DVM) students in regard to scientific papers. Methods: The authors studied DVM student behaviors across eight programs in North America using a web-based survey of closed- and open-ended questions about finding and evaluating scientific papers, including a task to read a linked scientific paper and answer questions about it. Results: A total of 226 individuals responded to the survey. The sections of a scientific paper that were most commonly read were the abstract, introduction, and conclusions. Students who reported reading a higher proportion of scientific papers were more likely to feel confident in their abilities to interpret them. A third of respondents answered open-ended questions after the paper reading task. Respondents felt the least amount of confidence with one of the final steps of evidence-based medicine, that of interpreting the significance of the paper to apply it in veterinary medicine. Conclusions: DVM students may lack the skills needed to evaluate scientific literature and need more practice and feedback in evaluating and interpreting scientific papers. Librarians who support DVM students can (1) help DVM students to efficiently evaluate scientific literature, (2) seek training opportunities in alternative modes of teaching and learning IL skills, and (3) partner with veterinary faculty and clinicians to provide students with practice and feedback in information evaluation. [ABSTRACT FROM AUTHOR]

Background: The GRADE-CERQual (Confidence in Evidence from Reviews of Qualitative research) approach has been developed by the GRADE (Grading of Recommendations Assessment, Development and Evaluation) Working Group. The approach has been developed to support the use of findings from qualitative evidence syntheses in decision-making, including guideline development and policy formulation. CERQual includes four components for assessing how much confidence to place in findings from reviews of qualitative research (also referred to as qualitative evidence syntheses): (1) methodological limitations, (2) coherence, (3) adequacy of data and (4) relevance. This paper is part of a series providing guidance on how to apply CERQual and focuses on a probable fifth component, dissemination bias. Given its exploratory nature, we are not yet able to provide guidance on applying this potential component of the CERQual approach. Instead, we focus on how dissemination bias might be conceptualised in the context of qualitative research and the potential impact dissemination bias might have on an overall assessment of confidence in a review finding. We also set out a proposed research agenda in this area.Methods: We developed this paper by gathering feedback from relevant research communities, searching MEDLINE and Web of Science to identify and characterise the existing literature discussing or assessing dissemination bias in qualitative research and its wider implications, developing consensus through project group meetings, and conducting an online survey of the extent, awareness and perceptions of dissemination bias in qualitative research.Results: We have defined dissemination bias in qualitative research as a systematic distortion of the phenomenon of interest due to selective dissemination of studies or individual study findings. Dissemination bias is important for qualitative evidence syntheses as the selective dissemination of qualitative studies and/or study findings may distort our understanding of the phenomena that these syntheses aim to explore and thereby undermine our confidence in these findings. Dissemination bias has been extensively examined in the context of randomised controlled trials and systematic reviews of such studies. The effects of potential dissemination bias are formally considered, as publication bias, within the GRADE approach. However, the issue has received almost no attention in the context of qualitative research. Because of very limited understanding of dissemination bias and its potential impact on review findings in the context of qualitative evidence syntheses, this component is currently not included in the GRADE-CERQual approach.Conclusions: Further research is needed to establish the extent and impacts of dissemination bias in qualitative research and the extent to which dissemination bias needs to be taken into account when we assess how much confidence we have in findings from qualitative evidence syntheses. [ABSTRACT FROM AUTHOR]

Background: The GRADE-CERQual (Confidence in Evidence from Reviews of Qualitative research) approach has been developed by the GRADE (Grading of Recommendations Assessment, Development and Evaluation) Working Group. The approach has been developed to support the use of findings from qualitative evidence syntheses in decision making, including guideline development and policy formulation. CERQual includes four components for assessing how much confidence to place in findings from reviews of qualitative research (also referred to as qualitative evidence syntheses): (1) methodological limitations, (2) coherence, (3) adequacy of data and (4) relevance. This paper is part of a series providing guidance on how to apply CERQual and focuses on making an overall assessment of confidence in a review finding and creating a CERQual Evidence Profile and a CERQual Summary of Qualitative Findings table.Methods: We developed this guidance by examining the methods used by other GRADE approaches, gathering feedback from relevant research communities and developing consensus through project group meetings. We then piloted the guidance on several qualitative evidence syntheses before agreeing on the approach.Results: Confidence in the evidence is an assessment of the extent to which a review finding is a reasonable representation of the phenomenon of interest. Creating a summary of each review finding and deciding whether or not CERQual should be used are important steps prior to assessing confidence. Confidence should be assessed for each review finding individually, based on the judgements made for each of the four CERQual components. Four levels are used to describe the overall assessment of confidence: high, moderate, low or very low. The overall CERQual assessment for each review finding should be explained in a CERQual Evidence Profile and Summary of Qualitative Findings table.Conclusions: Structuring and summarising review findings, assessing confidence in those findings using CERQual and creating a CERQual Evidence Profile and Summary of Qualitative Findings table should be essential components of undertaking qualitative evidence syntheses. This paper describes the end point of a CERQual assessment and should be read in conjunction with the other papers in the series that provide information on assessing individual CERQual components. [ABSTRACT FROM AUTHOR]

The World Health Organization has designated vaccine hesitancy and vaccine confidence among the most pressing issues in global health. The COVID-19 pandemic has made vaccine hesitancy and vaccine confidence particularly salient and urgent. The purpose of this special issue is to highlight a broad range of perspectives on these critical issues. We have included a total of 30 papers that address issues related to vaccine hesitancy and vaccine confidence across multiple levels of the Socio-Ecological Model. We have organized the empirical papers into the following sections: individual-level beliefs, minority health and health disparities, social media and conspiracy beliefs, and interventions. In addition to the empirical papers, three commentaries are included in this special issue. [ABSTRACT FROM AUTHOR]

The author presents comments on an article on a simulation model on sustainable and healthy diets for decision makers in 2021. Topics discussed include meat and dairy alternatives and the possible extension of the model boundary and understanding of transition policies, the expected tripling of insect market volume in Europe by 2023, and the environmental impacts of fertilizers and declining groundwater levels. Also noted is a suggested bipartisan approach on the food and health system.

Weakly supervised semantic segmentation, based on image-level labels, abandons the pixel-level labels relied upon by traditional semantic segmentation algorithms. It only utilizes images as supervision information, thereby reducing the time cost and human resources required for marking pixel data. The prevailing approach in weakly supervised segmentation involves two-step method, introducing an additional network and numerous parameters, thereby complicating the model structure. Furthermore, image-level labels typically furnishes only category information for the entire image, lacking specific location details and accurate target boundaries during model training. We propose an innovative One-Step Triple Enhanced weakly supervised semantic segmentation network(OSTE). OSTE streamlines the model structure, which can accomplish both pseudo-labels generation and semantic segmentation tasks in just one step. Furthermore, we augment the weakly supervised semantic segmentation network in three key aspects based on the class activation map construction method, thereby enhancing segmentation accuracy: Firstly, by integrating local information from the activation map with the image, we can enhance the network's localization and expansion capabilities to obtain more accurate and rich location information. Then, we refine the seed areas of the class activation map by exploiting the correlation between multi-level feature. Finally, we incorporate conditional random field theory to generate pseudo-labels with higher confidence and richer boundary information. In comparison to the prevailing two-step weakly supervised semantic segmentation schemes, the segmentation network proposed in this paper achieves a more competitive mean Intersection over Union (mIoU) score of 58.47% on Pascal VOC. Additionally, it enhances the mIoU score by at least 5.03% when compared to existing end-to-end schemes. [ABSTRACT FROM AUTHOR]

Presently, multi-label classification algorithms are mainly based on positive and negative logical labels, which have achieved good results. However, logical labeling inevitably leads to the label misclassification problem. In addition, missing labels are common in multi-label datasets. Recovering missing labels and constructing soft labels that reflect the mapping relationship between instances and labels is a difficult task. Most existing algorithms can only solve one of these problems. Based on this, this paper proposes a soft-label recover based label-specific features learning (SLR-LSF) to solve the above problems simultaneously. Firstly, the information entropy is used to calculate the confidence matrix between labels, and the membership degree of soft labels is obtained by combining the label density information. Secondly, the membership degree and confidence matrix are combined to construct soft labels, and this process not only solves the problem of missing labels but also obtains soft labels with richer semantic information. Finally, in the process of learning specific label features for soft labels. The local smoothness of the labels learned through stream regularization is complemented by the global label correlation, thus improving the classification performance of the algorithm. To demonstrate the effectiveness of the proposed algorithm, we conduct comprehensive experiments on several datasets. [ABSTRACT FROM AUTHOR]

Object detection via remote sensing encounters significant challenges due to factors such as small target sizes, uneven target distribution, and complex backgrounds. This paper introduces the K-CBST YOLO algorithm, which is designed to address these challenges. It features a novel architecture that integrates the Convolutional Block Attention Module (CBAM) and Swin-Transformer to enhance global semantic understanding of feature maps and maximize the utilization of contextual information. Such integration significantly improves the accuracy with which small targets are detected against complex backgrounds. Additionally, we propose an improved detection network that combines the improved K-Means algorithm with a smooth Non-Maximum Suppression (NMS) algorithm. This network employs an adaptive dynamic K-Means clustering algorithm to pinpoint target areas of concentration in remote sensing images that feature varied distributions and uses a smooth NMS algorithm to suppress the confidence of overlapping candidate boxes, thereby minimizing their interference with subsequent detection results. The enhanced algorithm substantially bolsters the model's robustness in handling multi-scale target distributions, preserves more potentially valid information, and diminishes the likelihood of missed detections. This study involved experiments performed on the publicly available DIOR remote sensing image dataset and the DOTA aerial image dataset. Our experimental results demonstrate that, compared with other advanced detection algorithms, K-CBST YOLO outperforms all its counterparts in handling both datasets. It achieved a 68.3% mean Average Precision (mAP) on the DIOR dataset and a 78.4% mAP on the DOTA dataset. [ABSTRACT FROM AUTHOR]

An informed search strategy based on random statistical analysis was developed for synchronous recognition of groundwater pollution source information and aquifer parameters. An informed search iterative course (ISIC) was accordingly designed, and each iteration included the determination of attempt point and state transition. In this paper, two improvement techniques were first adopted for choosing attempt points and judging state transition in ISIC to improve search efficiency and precision. The first improvement was that the variable radius free search method was applied to choosing the attempt point, and the size of the search radius was constantly adjusted in ISIC, taking the search ergodicity and efficiency into account. The second improvement technique was a Tsallis formula used for state transition judgment, and the controlled factor in the Tsallis formula was regulated continuously so that the search could consider ergodicity and efficiency simultaneously. Furthermore, frequent calls to the groundwater pollution numerical simulator to calculate the likelihood have inflicted a huge computational burden during ISIC. An effective way is to construct a substitute for emulating the simulator with a low calculating load. However, the mapping relation between the import and export of the numerical simulator was complex and had many variables. The precision of the substitute based on shallow learning is low sometimes. Therefore, we adopted the deep learning method and built an improved deep confidence network (DCN) substitute to emulate the highly nonlinear simulator. Finally, the synchronous recognition results for groundwater pollution source information and aquifer parameters were gained when ISIC ceased. The above-mentioned methods were verified in a case involving groundwater pollution. The consequence indicated that the ISIC with an improved DCN substitute can synchronously recognize groundwater pollution source information and aquifer parameters with a high degree of precision and efficiency. [ABSTRACT FROM AUTHOR]

The theory of mental models describes how human beings often make inductive inferences. That account is based on possibilities. It claims that, in inductions, people tend to prefer the possibility that seems to be more probable. The present paper tries to develop the account by proposing an additional quantitative method to determine which of the two possibilities in inductive processes is preferable. The paper resorts to a Non-Axiomatic Logic: NAL. NAL assigns quantitative values to the frequency and confidence of sentences. It also shows how those values can be transmitted from premises to conclusions in inductive inferences. This part of NAL is applied to the account of induction the theory of mental models gives. [ABSTRACT FROM AUTHOR]

Background: Health inequalities and poorer outcomes have been identified for patients with dark skin tones. The reasons are multi-factorial, but may include delayed treatment due to a lack of recognition of early clinical signs of physiological deterioration. Within the medical literature there is a light skin tone bias, leading to healthcare professionals having insufficient knowledge regarding the assessment of patients with different skin tones, which may result in reduced confidence and create patient safety issues. The aim of this scoping review was to explore the confidence levels of healthcare professionals when assessing patients of different skin tones. Methods: The methodology followed scoping review frameworks set out by Arksey and O'Malley (2005), the Joanna Briggs Institute (Peters et al., 2020) and the PRISMA extension for Scoping Reviews (PRISMA-ScR) (Tricco et al., 2018). Searches for literature were performed between February and June 2022 using electronic databases EBSCO (Academic Search Complete, the Allied Complementary Medicine Database, e-journals, MEDLINE, CINAHL), British Nursing Index (ProQuest), Scopus, Web of Science, Zetoc, UpToDate, Google Scholar, NICE Evidence, ResearchGate, Opengrey and the British Association of Dermatologists. No date range was specified, expanders were left on and the findings were screened using inclusion and exclusion criteria. Included papers were synthesised using narrative synthesis. Results: Thirteen papers were identified, and the extracted data charted by the paper's origin, sample size, profession and confidence levels. Our synthesis revealed reduced confidence in assessing, managing and diagnosing skin conditions in dark skin tones. A lack of training was cited by different health professionals, but undertaking tailored training and experiential learning increased confidence. Conclusions: There is a safety issue for patients with dark skin tones, as healthcare professionals lack clinical confidence in managing and treating all ethnicities equally. Tangible diversity within healthcare training is required, supported by inclusive skin tone imagery and appropriate terminology within medical literature. [ABSTRACT FROM AUTHOR]

Since the traditional ship stability failure probability assessment method has many input parameters and cumbersome intermediate calculation process, this paper proposes a joint multi-model machine learning prediction method based on confidence. The method calculates the confidence of each machine learning model for the current prediction result, selects the top n models among them, and takes the average of their prediction results as the output. The confidence is calculated by a method inspired by semi-supervised learning. To reduce the number of ship features that need to be input for assessment, a sensitivity analysis is used to reject irrelevant features. Eight machine learning models that have good performance and are widely used in other fields, including Radial Basis Function Neural Network, Random Forest, eXtreme Gradient Boosting, and so on, are used as component learners in this study. The hyperparameters of each model are obtained by cross-validation and grid search. The advancedness of the proposed method is verified by comparing it with other models on a small self-built ship stability failure probability dataset. By conducting experiments that simply average the results of the component learners, it is confirmed that simple superposition different models does not necessarily improve the accuracy. At the same time, after pre-processing the input features in different ways, the comparison of the prediction performance was conducted, and the experimental results showed that the proposed method is not affected by the way the input features are preprocessed and therefore has some robustness. [ABSTRACT FROM AUTHOR]

INTRODCTION: Listening strategy analysis and assessment not only need objective and fair sound listening strategy analysis, but also need high-precision and high real-time assessment model, and even more need in-depth analysis and feature extraction of the influencing factors of listening assessment. OBJECTIVES: To address the problems of current automatic assessment methods, such as non-specific application, poor generalization, low assessment accuracy, and poor real-time performance. METHODS: This paper proposes an automatic assessment method based on a deep confidence network based on crawfish optimization algorithm. First, the multi-dimensional listening strategy evaluation system is constructed by analyzing the listening improvement strategy; then, the depth confidence network is improved by the crayfish optimization algorithm to construct the automatic evaluation model; finally, through the analysis of simulation experiments. RESLUTS: The proposed method improves the evaluation accuracy, robustness, and real-time performance. The absolute value of the relative error of the automatic evaluation value of the proposed method is controlled in the range of 0.011, and the evaluation time is less than 0.005 s. The method is based on a deep confidence network based on the crayfish optimization algorithm. CONCLUSION: The problems of non-specific application of automated assessment methods, poor generalization, low assessment accuracy, and poor real-time performance are addressed. [ABSTRACT FROM AUTHOR]

How much should an entrepreneur experiment and when should they pivot? Do the answers to these questions change if the entrepreneur is subject to behavioral biases, such as overconfidence? In this paper, we develop a conceptual logic to address these questions. We focus on the design of a "program of experimentation," which we define as a sequentially interdependent set of experiments and pivot decisions an entrepreneur undertakes to develop a viable business idea. This conceptualization highlights two dimensions of program design: the number of experiments to run and the pivot threshold for evaluating experimental outcomes. Our computational model suggests that while experimenting and pivoting can improve new venture performance, it can also be taken too far. Programs of experimentation that generate frequent and early pivots may impede learning and underperform more conservative programs that generate fewer pivots. We also show that an effectively designed program of experimentation can partially remedy an entrepreneur's behavioral biases. Our work informs ongoing scholarly efforts to more fully understand the Lean Startup's strengths and limitations and advances the theoretical apparatus underlying a scientific approach to venturing. [ABSTRACT FROM AUTHOR]

Background: Advance care planning (ACP) is the process supporting individuals with life-limiting illness to make informed decisions about their future healthcare. Ethnic disparities in ACP have been widely highlighted, but interpretation is challenging due to methodological heterogeneity. This review aims to examine differences in the presence of documented ACP in individuals' care records for people with advanced disease by ethnic group, and identify patient and clinician related factors contributing to this. Methods: Mixed-methods systematic review. Keyword searches on six electronic databases were conducted (01/2000–04/2022). The primary outcome measure was statistically significant differences in the presence of ACP in patients' care records by ethnicity: quantitative data was summarised and tabulated. The secondary outcome measures were patient and clinician-based factors affecting ACP. Data was analysed qualitatively through thematic analysis; themes were developed and presented in a narrative synthesis. Feedback on themes was gained from Patient and Public Involvement (PPI) representatives. Study quality was assessed through Joanna Briggs Institute Critical Appraisal tools and Gough's Weight of Evidence. Results: N=35 papers were included in total; all had Medium/High Weight of Evidence. Fifteen papers (comparing two or more ethnic groups) addressed the primary outcome measure. Twelve of the fifteen papers reported White patients had statistically higher rates of formally documented ACP in their care records than patients from other ethnic groups. There were no significant differences in the presence of informal ACP between ethnic groups. Nineteen papers addressed the secondary outcome measure; thirteen discussed patient-based factors impacting ACP presence with four key themes: poor awareness and understanding of ACP; financial constraints; faith and religion; and family involvement. Eight papers discussed clinician-based factors with three key themes: poor clinician confidence around cultural values and ideals; exacerbation of institutional constraints; and pre-conceived ideas of patients' wishes. Conclusions: This review found differences in the presence of legal ACP across ethnic groups despite similar presence of informal end of life conversations. Factors including low clinician confidence to deliver culturally sensitive, individualised conversations around ACP, and patients reasons for not wishing to engage in ACP (including, faith, religion or family preferences) may begin to explain some documented differences. Trial registration: PROSPERO-CRD42022315252. [ABSTRACT FROM AUTHOR]

Contemporary healthcare for those experiencing mental illness requires healthcare practitioners (HCPs) to effectively incorporate the prescription of exercise in their treatment, in accordance with clinical guidelines. However, there has been a lack of effective implementation of such recommendations. The purpose of this review was to identify barriers to exercise prescription in the treatment of people diagnosed with mental illness as perceived by HCPs. APA PsycINFO, CINAHL, MEDLINE, and PubMed electronic databases were searched for relevant articles published in the period from January 2005 to September 2023. A total of 18 papers were included for thematic synthesis. Four key themes were identified across the qualitative (8), quantitative (6), and mixed method (4) papers, including a lack of knowledge and confidence of HCPs in prescribing exercise; role and responsibility; HCPs' misconceptions of client barriers; and systemic issues impacting exercise prescription practices. A lack of knowledge or confidence was the most common barrier. Some HCPs indicated a desire to develop their skills in exercise prescription, while others indicated a preference for an exercise professional to take responsibility for this aspect of treatment. Systemic barriers were spread across a range of issues, with lack of time, excessive workload, and difficulties accessing qualified staff most commonly cited. This review provides further insight into the barriers to exercise prescription faced by HCPs and makes recommendations regarding how to address these barriers in order to better implement clinical guidelines and thus improve the quality of treatment provided to people diagnosed with a mental illness. [ABSTRACT FROM AUTHOR]

Based on the examples of Judge Deborah from the Old Testament and Pastor/Teacher Priscilla from the New Testament, this paper contends that women have a biblical responsibility to lead in any vocation for which God has called and anointed them, and the Christian church has a biblical responsibility to accept and encourage them. Women leaders offer valuable leadership qualities, as illustrated by Deborah, the prophetic judicial/governmental/military leader of a nation, and Priscilla, the theologian, educator, missionary, and pastor in the nascent church. This paper further argues that leadership structures are not complete or fully effective without feminine inclusion and participation. The church and the world have historically deprived themselves of rich resources by curtailing women's leadership roles. The need for rediscovering and recovering women's leadership gifts and styles has never been more urgent or appropriate in the current cultural atmosphere requiring an emphasis on collaboration and cooperation (relationality), emotional intelligence that seeks transformation rather than transaction, and servant leadership, as manifested in Deborah and Priscilla as leaders. The church would be wise to embrace the Deborahs and Priscillas, as well as other types of women leaders whomGod has placed in her midst, thus creating strong, responsive, and nurturing communities that reflect Jesus to the world. [ABSTRACT FROM AUTHOR]

In the past few years, significant advancements in microscopic imaging technology have led to the production of numerous high-resolution images capturing brain neurons at the micrometer scale. The reconstructed structure of neurons from neuronal images can serve as a valuable reference for research in brain diseases and neuroscience. Currently, there lacks an accurate and efficient method for neuron reconstruction. Manual reconstruction remains the primary approach, offering high accuracy but requiring significant time investment. While some automatic reconstruction methods are faster, they often sacrifice accuracy and cannot be directly relied upon. Therefore, the primary goal of this paper is to develop a neuron reconstruction tool that is both efficient and accurate. The tool aids users in reconstructing complete neurons by calculating the confidence of branches during the reconstruction process. The method models the neuron reconstruction as multiple Markov chains, and calculates the confidence of the connections between branches by simulating the reconstruction artifacts in the results. Users iteratively modify low-confidence branches to ensure precise and efficient neuron reconstruction. Experiments on both the publicly accessible BigNeuron dataset and a self-created Whole-Brain dataset demonstrate that the tool achieves high accuracy similar to manual reconstruction, while significantly reducing reconstruction time. [ABSTRACT FROM AUTHOR]

The purpose of this study is to provide an overview of patients' experiences using a precision medicine (PM) clinic that conducts pharmacogenomics-based (PGx) testing for adverse drug reactions. The study aimed to identify the features of the clinic valued most by patients and areas for improvement. A paper survey was used to collect data. Survey questions focused on patients' perceptions of the PM testing and the overall clinic experience. Sixty-seven patients completed the survey. Quantitative data were analyzed using SPSS and frequencies were reported. Open-ended responses were coded and organized thematically. Patients reported that the clinic services increased confidence in their medication usage. Feeling respected by staff, receiving education, and quick appointments were highly valued by patients. Suggested areas for improvement included better communication from the clinic to patients, expansion of clinic services, and education for other healthcare providers. The findings demonstrate that patient experience goes beyond the clinical care provided. Current and potential future providers of PM should invest the time and energy to configure their care delivery system to enhance the patient experience. [ABSTRACT FROM AUTHOR]

Introduction: Nursing educators face challenges in helping registered nurses prepare to be psychiatric nurse practitioners. Nursing educators must consider the variation of students' skill sets, experience levels, and the shortage of preceptors. Simulations can help overcome limited clinical sites and standardize skill acquisition. High-fidelity simulations can be helpful but are labor-intensive and expensive. Low-fidelity simulations are adaptable to fit the learning needs of psychiatric nurse practitioner students but little research has evaluated these simulations. Objective: This paper evaluates a series of low-fidelity interventions used to help students learn diagnostic criteria, treatment decisions, and documentation. Methods: A retrospective descriptive analysis was performed on the results of all students in five cohorts in a psychiatric nurse practitioner course (n =68) on 45 low-fidelity online simulations over five years during the course on advanced psychiatric nursing of adults. Diagnostic notes were graded on four criteria by a psychologist or a psychiatric nurse practitioner. A representative sample of grades on eight notes were analyzed for this manuscript. Survey responses from the students in one cohort were obtained to evaluate their confidence levels and perceptions of simulation utility and responses were analyzed using descriptive and qualitative methods. Results: The overall mean of description, detail, completeness, and professionalism increased from 7.6 (out of 10) to 9 over the semester with statistically significant improvements in all four areas. The strongest correlation was between detail and completeness and the weakest correlation was between professionalism and description. Students reported that they found significant value in the low-fidelity simulation exercises. Conclusion: This analysis demonstrates one of the first efforts to analyze low-fidelity simulations for psychiatric nurse practitioner students. The data indicate these simulations can help students improve their confidence and skills in several areas. [ABSTRACT FROM AUTHOR]