Tool For Qualitative Analysis Research Articles

Prediction of Flash Point of Materials Using Bayesian Kernel Machine Regression Based on Gaussian Processes With LASSO‐Like Spike‐and‐Slab Hyperprior

ABSTRACTThe determination of flash points is a critical aspect of chemical safety, essential for assessing explosion hazards and fire risks associated with flammable solutions. With the advent of new chemical blends and the increasing complexity of chemical waste management, the need for accurate and reliable flash point prediction methods has become more pronounced. This study introduces a novel predictive approach using Bayesian kernel machine regression (BKMR) with Gaussian process priors, designed to meet the growing demand for precise flash point estimation in the context of chemical safety. The BKMR model, underpinned by Bayesian statistics, offers a comprehensive framework that not only quantifies prediction uncertainty but also enhances interpretability amidst experimental data variability. Our comparative analysis reveals that BKMR surpasses traditional predictive models, including support vector machines, kernel ridge regression, and Gaussian process regression, in terms of accuracy and reliability across multiple metrics. By elucidating the intricate interactions between molecular features and flash point properties, the BKMR model provides profound insights into the chemical dynamics that influence flash point determinations. This study signifies a methodological leap in flash point prediction, offering a valuable tool for chemical safety analysis and contributing to the development of safer chemical handling and storage practices.

Linguistic encoding of women’s agency in the German political discourse on abortion: A diachronic Critical Discourse Analysis

This research, rooted in the Critical Discourse Analysis framework, employs a mixed-methods approach to examine debates on abortion legislation in the German Bundestag. Focusing on the attribution of agency to women through semantic role assignment in the context of abortion procedures, the study utilises both qualitative analysis and quantitative data analysis techniques. Five debates spanning the 1970s, 1990s and 2010s were examined using the qualitative analysis tool MAXQDA. Results consistently indicate that arguments referring to women are predominantly assigned semantic roles associated with passivity and relatively low agency. This pattern persists regardless of the ideological stance, transcending divides between pro-life and pro-choice advocates. This perpetuates and reinforces the societal perception of women as passive, upholding a traditional gender stereotype within the discourse. A larger number of arguments referring to women were found in the pro-choice data compared to the pro-life data, indicating a greater emphasis on women within the argumentation of pro-choice speakers. The study underscores the enduring impact of language on shaping perceptions of women’s agency in the context of abortion legislation debates.

CACTI: an in silico chemical analysis tool through the integration of chemogenomic data and clustering analysis

It is well-accepted that knowledge of a small molecule’s target can accelerate optimization. Although chemogenomic databases are helpful resources for predicting or finding compound interaction partners, they tend to be limited and poorly annotated. Furthermore, unlike genes, compound identifiers are often not standardized, and many synonyms may exist, especially in the biological literature, making batch analysis of compounds difficult. Here, we constructed an open-source annotation and target hypothesis prediction tool that explores some of the largest chemical and biological databases, mining these for both common name, synonyms, and structurally similar molecules. We used this Chemical Analysis and Clustering for Target Identification (CACTI) tool to analyze the Pathogen Box collection, an open-source set of 400 drug-like compounds active against a variety of microbial pathogens. Our analysis resulted in 4,315 new synonyms, 35,963 pieces of new information and target prediction hints for 58 members.Scientific contributionsWith the employment of this tool, a comprehensive report with known evidence, close analogs and drug-target prediction can be obtained for large-scale chemical libraries that will facilitate their evaluation and future target validation and optimization efforts.

Balancing Social and Cultural Priorities in the UN 2030 Sustainable Development Goals (SDGs) for UNESCO World Heritage Cities

There is a strong relationship between heritage-led urban regeneration and the UN initiatives for Sustainable Development (SD). These include the Intangible Cultural Heritage Convention (ICH; 2003) and Historic Urban Landscape (HUL; 2011) under the UNESCO mandate and the Sustainable Development Goals (SDGs; 2015) and the New Urban Agenda (NUA; 2016) under the UN mandate. Despite the presence of those initiatives, regeneration in a World Heritage city often leads to the disappearance of intangible heritage, gentrification, excessive tourism, and social exclusion. Therefore, this paper critically identifies the shortcomings of those initiatives in addressing social and cultural sustainability. It uses the recently inscribed city of As-Salt on the WHL to showcase how the relevant SDGs’ targets and indicators are problematic in monitoring and measuring the sustainability of urban regeneration practices in WH cities. This is achieved by investigating where heritage and culture are embedded within the descriptions of goals and indicators in the three initiatives (SDGs, NUA, and HUL) document. A content analysis, using the NVivo qualitative data analysis tool, was conducted in order to identify complementarity, synergies, and correlations among the goals and indicators related to social and cultural sustainability. This paper concludes by suggesting an integrated approach under the umbrella of the SDGs for a more sustainable heritage-led urban regeneration alternative for cities acquiring UNESCO WH status.

Prediction of Vacuum Ultraviolet/Ultraviolet Gas-Phase Absorption Spectra Using Molecular Feature Representations and Machine Learning.

Ultraviolet (UV) absorption spectroscopy is a widely used tool for quantitative and qualitative analyses of chemical compounds. In the gas phase, vacuum UV (VUV) and UV absorption spectra are specific and diagnostic for many small molecules. An accurate prediction of VUV/UV absorption spectra can aid the characterization of new or unknown molecules in areas such as fuels, forensics, and pharmaceutical research. An alternative to quantum chemical spectral prediction is the use of artificial intelligence. Here, different molecular feature representation techniques were used and developed to encode chemical structures for testing three machine learning models to predict gas-phase VUV/UV absorption spectra. Structure data files (.sdf) and VUV/UV absorption spectra for 1397 volatile and semivolatile chemical compounds were used to train and test the models. New molecular features (termed ABOCH) were introduced to better capture pi-bonding, aromaticity, and halogenation. The incorporation of these new features benefited spectral prediction and demonstrated superior performance compared to computationally intensive molecular-based deep learning methods. Of the machine learning methods, the use of a Random Forest regressor returned the best accuracy score with the shortest training time. The developed machine learning prediction model also outperformed spectral predictions based on the time-dependent density functional theory.

FRAMING ANALYSIS OF MEDIA ONLINE INDONESIA AGAINTS EXECUTIONS WITHOUT NOTIFICATIONS BY THE GOVERNMENT OF SAUDI ARABIA

This study aims to analyze the views of online media in Indonesia on the case of the execution without notification carried out by Saudi Arabia against Tuti Tursilawati, who is a worker from Indonesia. The researcher uses Murray Edelman's framing analysis theory to analyze media texts to determine how a media conveys news. The research method used is qualitative research with literature review and literature review. Data was collected by accessing three online news portals in Indonesia, including Detik, Kompas, and CNN and obtaining a total of 75 news articles. The news was collected using NCapture and analyzed using NVIVO 12 plus software as a qualitative data analysis tool using features such as crosstab and matrix coding. The research results show that three online media in Indonesia reporting on executions without notification tend to discuss the flawed system and method of communication in Saudi Arabia rather than focusing on Indonesia's failure to save Tuti Tursilawati from execution. Even though the government has sought legal assistance for Tuti Tursilawati, the lack of advocacy and weak political lobbying meant that the execution could not be thwarted. However, this important matter should have been discussed in the media. Based on the results of analysis from 3 online media and 3 points of research using Murray Edelman's overall framing analysis, it tends to corner Saudi Arabia so that it seems that the media is not delivering neutral news but is in favour of the government. This also seems exaggerated because most news highlights the lousy side of Saudi Arabia, so the government's shortcomings in handling it are of little concern.

Self-Assembly of Strain-Adaptable Surface-Enhanced Raman Scattering Substrate on Polydimethylsiloxane Nanowrinkles.

Flexible surface-enhanced Raman scattering (SERS) substrates adaptable to strains enable effective sampling from irregular surfaces, but the preparation of highly stable and sensitive flexible SERS substrates is still challenging. This paper reports a method to fabricate a high-performance strain-adaptable SERS substrate by self-assembly of Au nanoparticles (AuNPs) on polydimethylsiloxane (PDMS) nanowrinkles. Nanowrinkles are created on prestrained PDMS slabs by plasma-induced oxidation followed by the release of the prestrain, and self-assembled AuNPs are transferred onto the nanowrinkles to construct the high-performance SERS substrate. The results show that the nanowrinkled structure can improve the surface roughness and enhance the SERS signals by ∼4 times compared to that of the SERS substrate prepared on flat PDMS substrates. The proposed SERS substrate also shows good adaptability to dynamic bending up to ∼|0.4| 1/cm with excellent testing reproducibility. Phenolic pollutants, including aniline and catechol, were quantitatively tested by the SERS substrate. The self-assembled flexible SERS substrate proposed here provides a powerful tool for chemical analysis in the fields of environmental monitoring and food safety inspection.

The reception of post-Soviet Russian fiction through the peritexts of Finnish translations

ABSTRACT This article is based on research addressing the reception of post-Soviet Russian fiction in the twenty-first century (2000–2023) through Finnish translations and the notions of Russia and Russian literature mediated through them. The investigation of translated fiction draws on imagology, i.e. the study of images and cross-national perceptions in literary representations. Focusing on the peritexts, a subcategory of paratexts coined by Genette (1987/1997), the article investigates book cover texts and publishers’ descriptions of the translated works to find out how the translations are received and introduced to readers of the target culture. The translations comprise 101 books, first translated during 2000–2023. The peritexts were retrieved directly from the printed books or using the search service Finna.fi and publisher websites. The analysis was conducted with help of a computer-assisted qualitative data analysis tool, designed to support inductive, data-driven qualitative analysis. As a result of the analysis, three thematic groups emerging from the peritexts were identified: 1) the portrayal of the (Soviet) Russian past and post-Soviet society as grim, insane and tragic, 2) the emphasis on realism and truthfulness of the image of Russia conveyed by the translations, and 3) praise of the authors’ literary skills.

Exploring Internal Reverse Migration Patterns in Cumilla District, Bangladesh: A Case Study During the COVID-19 Pandemic

The study possesses two-fold objectives: first, to explain the nature of internal reverse migration in Bangladesh during the COVID-19 pandemic, and second, to explore the push-pull factors of it. This study used a qualitative analysis tool and conducted 04 case studies and 10 In-depth interviews of reverse migrants for case study-based analysis. the study found that the pandemic triggered the reverse migration of informal workers, particularly female workers. Livelihood crisis, food insecurity, unexpected shocks, health insecurity, low living costs, and fear of infection are push-pull factors of reverse migration during COVID-19. Furthermore, these push-pull factors have motivated informal workers to migrate from urban to rural areas during COVID-19. The findings recommend that policymakers should address the vulnerability of informal workers in policy decisions. Policymakers should introduce new programs, i.e., social protection, and emergency economic schemes to provide support to the informal workers during emergencies like COVID-19.

A Comprehensive Review on Advantages of Ultra Performance Liquid Chromatography (UPLC) for Analytical Method Development, Validation, and Stability Studies

Ultra Performance Liquid Chromatography (UPLC) represents a paradigm shift in analytical separation science, offering enhanced speed, sensitivity, and resolution while retaining the foundational principles of traditional liquid chromatography. This comprehensive review explores the principles, instrumentation, advantages, and applications of UPLC in analytical method development, validation, and stability studies, with a focus on pharmaceutical analysis. UPLC leverages finer particles and intensified flow rates to achieve unprecedented performance gains, facilitating rapid and precise separations without compromising analytical rigor. The discussion delves into the intricate instrumentation involved, including sample injection, column selection, and detector operation, highlighting the critical role of each component in ensuring optimal analytical performance. Advantages of UPLC include drastically reduced run times, streamlined method optimization, and increased sample throughput, while limitations such as higher back pressures and limited column regenerability are also discussed. Furthermore, the review outlines the diverse applications of UPLC across pharmaceutical, environmental, food and beverage, clinical, forensic, bioanalytical, and polymer analysis domains, underscoring its versatility and significance in advancing research, development, and quality control in various industries. In summary, UPLC represents a transformative tool in analytical chemistry, offering unparalleled capabilities for expedited and accurate analysis of complex sample matrices, ultimately driving innovation and scientific progress. Key Words: Ultra Performance Liquid Chromatography (UPLC), analytical method development, validation, stability studies, pharmaceutical analysis, instrumentation, advantages, applications, sample injection, column chemistry, detector technology, back pressures, method optimization, sample throughput, environmental analysis, food and beverage analysis, clinical diagnostics, forensic analysis, bioanalytical research, polymer analysis, analytical chemistry.

Analysis and Control of Partially Observed Discrete-Event Systems via Positively Constructed Formulas

This paper establishes a connection between control theory for partially observed discrete-event systems (DESs) and automated theorem proving (ATP) in the calculus of positively constructed formulas (PCFs). The language of PCFs is a complete first-order language providing a powerful tool for qualitative analysis of dynamical systems. Based on ATP in the PCF calculus, a new technique is suggested for checking observability as a property of formal languages, which is necessary for the existence of supervisory control of DESs. In the case of violation of observability, words causing a conflict can also be extracted with the help of a specially designed PCF. With an example of the problem of path planning by a robot in an unknown environment, we show the application of our approach at one of the levels of a robot control system. The prover Bootfrost developed to facilitate PCF refutation is also presented. The tests show positive results and perspectives for the presented approach.

Negotiating access and belonging: Recounting the lived experiences and challenges of migrant women returnees in Nigeria

The study explores the lived experiences of women migrant returnees in Nigeria. It aims to highlight the motivation and push factors for migration, understand the challenges and lived experiences of migrant women, and appraise their integration and sense of belonging. Through referrals and purposive sampling, a total of 20 migrant women were recruited and interviewed. The inclusion criteria include those who have lived and worked in the diaspora for a minimum of 5 years and 2 years as a returnee in Nigeria, respectively. The exclusion criteria involve women who migrated with families and those considered professionals. Themes were identified with the NVivo (v.12) qualitative software and the Content Qualitative Analytical tool employed to interpret these themes. The need for migration for many women includes access to improved economic life, infrastructure, and amenities, means of sustaining families in the home country, and improved social and political security. The lived experience of women migrants in the diaspora includes sexual harassment, rape, forced and inhumane labour practices, low wages, isolation and depression, and xenophobia. For many returnees, the challenge includes unemployment, integration, family support, inflation, and financial insolvency. The quest for integration and belonging is limited for many returnees. The paper argues for more robust migration policies and a well-established policy of integration for migrant returnees. The study recommends a more monitoring effort of the activities of the Nigerian border. This recommendation becomes crucial with the porous borders in Nigeria through which people, including women, migrate to other countries illegally and undocumented.

Leveraging Artificial Intelligence (AI) As a Critical Friend: The Affordances and Limitations

ABSTRACT This qualitative self-study contributes new insights on critical friendship, specifically related to Artificial Intelligence (AI) chatbot utility trends, asking: In what ways can AI serve as our critical friend? And, what are the affordances and limitations of AI as a critical friend, compared to our human critical friends? To answer these questions, the authors selected Pi.ai/talk, an AI tool they later nicknamed Pia. After interacting with Pia (using data from a previous study), they compared Pia’s responses to those of two human critical friends, Anne and Anders, who originally provided feedback in their previous self-study. Drawing on theoretical and conceptual perspectives (Thought Collective, Anatomy of Critical Friend Attributes, & Critical Friend Definition Continuum) and using four data sources, the authors applied multiple qualitative analysis tools to determine the affordances and limitations of Pia. They found Pia could serve as a critical friend when examining her critical friend attributes because to some extent she provided feedback to their thinking, probed thoughtful questions, and remained in a positive tone. Although Pia had some affordances in her ability to serve as a critical friend, the data evidenced several limitations in how she met the critical attributes in the areas of constraints, trust, and relational dynamics; especially when juxtaposing Pia’s feedback to Anne’s and Anders’ feedback. Given the findings, the authors argue AI tools can complement human critical friends in self-study research, but as of the date of this publication, they do not advocate for replacing human critical friends entirely.

Swept-source Raman spectroscopy of chemical and biological materials.

Raman spectroscopy has been used as a powerful tool for chemical analysis, enabling the noninvasive acquisition of molecular fingerprints from various samples. Raman spectroscopy has proven to be valuable in numerous fields, including pharmaceutical, materials science, and biomedicine. Active research and development efforts are currently underway to bring this analytical instrument into the field, enabling in situ Raman measurements for a wider range of applications. Dispersive Raman spectroscopy using a fixed, narrowband source is a common method for acquiring Raman spectra. However, dispersive Raman spectroscopy requires a bulky spectrometer, which limits its field applicability. Therefore, there has been a tremendous need to develop a portable and sensitive Raman system. We developed a compact swept-source Raman (SS-Raman) spectroscopy system and proposed a signal processing method to mitigate hardware limitations. We demonstrated the capabilities of the SS-Raman spectroscopy by acquiring Raman spectra from both chemical and biological samples. These spectra were then compared with Raman spectra obtained using a conventional dispersive Raman spectroscopy system. The SS-Raman spectroscopy system used a wavelength-swept source laser (822 to 842nm), a bandpass filter with a bandwidth of 1.5nm, and a low-noise silicon photoreceiver. Raman spectra were acquired from various chemical samples, including phenylalanine, hydroxyapatite, glucose, and acetaminophen. A comparative analysis with the conventional dispersive Raman spectroscopy was conducted by calculating the correlation coefficients between the spectra from the SS-Raman spectroscopy and those from the conventional system. Furthermore, Raman mapping was obtained from cross-sections of swine tissue, demonstrating the applicability of the SS-Raman spectroscopy in biological samples. We developed a compact SS-Raman system and validated its performance by acquiring Raman spectra from both chemical and biological materials. Our straightforward signal processing method enhanced the quality of the Raman spectra without incurring high costs. Raman spectra in the range of 900 to were observed for phenylalanine, hydroxyapatite, glucose, and acetaminophen. The results were validated with correlation coefficients of 0.88, 0.84, 0.87, and 0.73, respectively, compared with those obtained from dispersive Raman spectroscopy. Furthermore, we performed scans across the cross-section of swine tissue to generate a biological tissue mapping plot, providing information about the composition of swine tissue. We demonstrate the capabilities of the proposed compact SS-Raman spectroscopy system by obtaining Raman spectra of chemical and biological materials, utilizing straightforward signal processing. We anticipate that the SS-Raman spectroscopy will be utilized in various fields, including biomedical and chemical applications.

China-ASEAN Economic Ties: Balancing Growth amid Middle-Income Challenges and Opportunities

The introduction of a free trade area between the Association of Southeast Asian Nations (ASEAN) and China (ACFTA) in 2012 brought China to a leading economic position in Southeast Asia (this was manifested in a significant, almost 2.2-fold, increase in the volume of trade) and turned it into a driving force of ASEAN’s economic prosperity. However, this increased economic interdependence creates challenges for both China and ASEAN: on the one hand, China seeks to make the transition from a high-income country to sustainable economic development in the ASEAN region, and on the other hand, ASEAN has concerns about excessive economic dependence on China. This situation requires a balance to be struck to avoid repeating the historical patterns seen in Japan in the 1960s and 1980s. This article examines the investment, trade and geopolitical relations between China and ASEAN in a historical retrospective of 2010-2022, assesses their economic dependence and the mechanisms of political-economic relations, identifies the factors that caused China’s rapid economic breakthrough, and outlines directions for overcoming the most modern challenges that have place in the context of this relationship through formulation of suggested frameworks. The article considers 2 research questions, for the solution of which the G/T (Grounded Theory) approach was used and a qualitative analysis of the 12 most relevant sources was carried out (limitation of their number – according to the concept of theoretical saturation), selected primarily through online databases, websites, international organizations’ data, analytical reviews, and scientific papers. RQ1: Identify the root causes of the problems faced by ASEAN middle-income countries in their engagement with China. The article identifies the following 3 main reasons through the empirical review analysis: 1) dependence of middle-income ASEAN countries on financial assistance, especially from China; 2) a noticeable decrease in unity in the ASEAN region; 3) China’s lack of recommendations on the advisory policy of economic development in the ASEAN countries. RQ2: development of recommendations for middle-income ASEAN countries to increase their ability to pave independent paths to sustainable economic development and reduce their economic dependence on China, taking into account the review of the balance of power in political relations with the United States and China. Using the qualitative analysis tool ATLAS.ti (version 24) for the G/T approach, it was concluded that to overcome the syndromes of lower-middle-income trap (LMIT) and higher-middle-income trap (HMIT), ASEAN economies should implement the following spontaneous strategies: infrastructure development, improvement of basic education and promotion of science and technology. In addition, it is important to raise awareness of political tensions between China and the US, apply the techniques of thoughtful diplomacy, fine-tuned policy formulation, and shared vision to establish a diplomatic balance between China, the US, and Japan in the context of geopolitical risk management.

Study of the Effect of Procedural Justice on Performance

This paper aims to identify research trends on procedural justice on performance globally. The method used in this study is qualitative research with a bibliometric analysis. As for the data found, 122 documents were obtained and analyzed from 2014-2023. This dataset was converted to CSV format and for Bibliometrix in the analysis using VOSviewer. The study included publication distribution year, country, keywords, and authors. The findings of this research showed that the research trend from 2014 to 2023 Experienced a significant increase in interest and research related to procedural justice on performance. The United States is the country that contributes the most research publications, research trends show an increasing focus throughout this decade. The increasing focus on procedural justice on performance reflects a paradigm shift in understanding and dealing with the challenges and opportunities faced by organizations in applying the principles of procedural justice used in organizations to their employees. The main limitation of this study should be considered - the use of data derived only from the Scopus database. This paper reveals research trends and areas of procedural justice on performance over the past few years. The results can help organisations to quickly understand procedural justice in performance research. This paper also provides an alternative approach in conducting literature reviews with qualitative research analysis tools that were previously widely adopted in various disciplines and are relatively new compared to conventional systematic literature

Greenness-sustainability metrics for assessment smart-chemometric spectrophotometric strategy for evaluation of the combination of six gastric proton-pump inhibitors with two selected impurities

Green analytical approaches are employed for the determination of active pharmaceutical ingredients, in conjunction with their impurities. Smart chemometric spectrophotometric techniques, including orthogonal partial least square (OPLS), variable selection such as genetic algorithm (GA-OPLS), and interval selection (i-OPLS), were utilized. These chemometric models were implemented for assessing six proton-pump inhibitors Omeprazole, Esomeprazole, Lansoprazole, Pantoprazole, Rabeprazole, and Dexlansoprazole along with two selected official impurities, namely 4-Desmethoxy omeprazole impurity and Rabeprazole-impurity B. Experimental design was implemented to separate impurities, in the process of multivariate calibration, a five-level eight-factor calibration design consisting of 25 samples was selected. This design was deliberately selected to guarantee that the components were mutually orthogonal to assess the model's performance and reliability, a separate validation set of 15 samples was constructed. The best-performing of the proposed techniques were identified by considering the least favorable values of the Correlation Coefficient (R ≥ 0.9995), the Root Mean Square Error of Prediction (RMSEP) values between (0.0102–0.5622), and the Relative Error of Prediction (REP) values between (0.2961–1.1917). The proposed and reported methods' greenness-sustainability was quantitatively evaluated, and a comparative study of the greenness profile was established through a spider chart, the National Environmental Method Index tool, advanced and modified NEMI along with the Hexagon tool, and the whiteness qualities of the presented approaches were assessed by implementing the recently adopted Red-Green-Blue paradigm and White Analytical Chemistry tool. These approaches are well-suited for use in quality control laboratories due to their observed acceptance, long-term sustainability, simplicity, and affordability.

Implementing trauma-informed care practices in the workplace: a descriptive phenomenological study

The effects of trauma are becoming more prevalent in the clinical setting, which has helped generate conversations about being more trauma-informed and providing trauma-informed care services. The principles centered around trauma-informed care could be applied to a person’s everyday life, including the work setting with the goal of creating a more trauma-informed environment for all employees. This qualitative descriptive phenomenological study aimed to investigate what trauma-informed care principles are needed in the workplace from the employee perspective to create a more trauma-informed environment. The survey instrument used in this study was a modified version of Fallot and Harris’s (2011) consumer satisfaction survey in their published article Creating Cultures of Trauma-Informed Care: A Self-Assessment and Planning Protocol. The instrument contained 13 questions, with each core question having an optional secondary question requesting additional details about the participants’ responses. The tool was categorized into four sections: safety, trustworthiness, choice and collaboration, and empowerment. Ninety participants accessed the survey through SurveyMonkey Audience, but four did not meet the criteria to participate and exited the study. The researcher was left with 86 completed surveys. The qualitative analytical tool Quirkos was employed to help analyze the data and generate themes. The category that produced the most themes was empowerment. Employees want to be viewed as a person rather than a resource to get the job done. Likewise, participants wanted to be valued and have their voices heard. To push this conversation forward, future researchers should conduct interviews face-to-face to produce more in-depth findings.

Development of a Qualitative Data Analysis Codebook for Arterial Hypertension and Type-2-Diabetes Integrated Care Evaluation.

Non-communicable diseases, such as arterial hypertension (HTN) and type-2 diabetes (T2D), pose a global public health problem. Integrated care with focus on person-centred principles aims to enhance healthcare quality and access. Previous qualitative research has identified facilitators and barriers for scaling-up integrated care, however the lack of standardized terms and measures hinder cross-country comparisons. This paper addresses these gaps by presenting a generic codebook for qualitative research on integrated care implementation for HTN and T2D. The codebook serves as a tool for deductive or deductive-inductive qualitative analysis, organizing concepts and themes from qualitative data. It consists of nine first level and 39 second level themes. First level codes cover core issues; and second level codes provide detailed insights into facilitators and barriers. This codebook is more widely applicable than previously developed tools because it includes a broader scope of stakeholders across micro, meso, and macro levels, and the themes being derived from highly diverse health systems across high- and low-income countries. The codebook is a useful tool for implementation research on integrated care for HTN and T2D at global scale. It facilitates cross-country learning, contributing to improved implementation, scale-up and outcomes.

A depth-resolved quantitative evaluation method for non-carious cervical lesions treatment with optical coherence tomography

ObjectivesThe aim of this study is prognostic assessment of surface smoothness and the presence of internal bubbles after treatment of non-cancerous cervical lesions (NCCLs) using optical coherence tomography (OCT). MethodsAfter treatment with NCCLs, cross-sectional images of the lesion parts of the sample were non-invasively acquired and analyzed. The surface smoothness between tooth and resin, resin and cemento-enamel junction, and the presence bubble inside resin was confirmed. In addition, using an algorithm that distinguishes between resin and dental structure based on OCT cross-sectional images, we quantitatively analyzed the amount of resin used in treating NCCLs and acquired 3D images. ResultsThe inner structure of the resin in each sample was checked, and the presence of bubbles was confirmed. In addition, the resin sections were separated from the tomographic images acquired by OCT to visualize 3D images. The volume of resin used in the treatment part of each NCCLs samples was quantitatively analyzed as 3.7216 ∼ 14.889 mm3. ConclusionsOCT is able to measure not only the surface abrasion provided by existing intraoral scanner, but also the size and depth location of interal bubbles, which is distinctive advantage of our method. Based on our results, OCT is a significant tool for qualitative and quantitative analysis of dental NCCLs treatment before and after treatment. Clinical significanceThe study used OCT, a non-destructive diagnostic, to reveal the structure of the resin and the location and size of bubbles after NCCLs treatment. These findings could be golden standard in determining the prognosis of NCCLs treatment.