Data Analysis Software Research Articles

Sociological Study of Deurbanization Through Sustainable Village Development in Indonesia

This study aimed to analyze deurbanization through sustainable village development from a sociological perspective. The study was conducted in Bantaeng Regency, South Sulawesi, Indonesia. This area was selected because sustainable village development can change the number of "underdeveloped" and "very underdeveloped" villages into "developed" and "independent". A qualitative method was adopted to explore sustainable village development by referring to the village development index (IDM), namely social, economic, and environmental resilience. Data were collected through in-depth interviews with informants selected using purposive sampling. The data include elements of village government, community institutions, and society, such as community leaders, educators, religion, youth, traders, farmers, as well as representatives of women and poor groups. Observations were carried out at the study location while collecting documents related to regulations and reports on sustainable village development. The Qualitative Data Analysis (QDA) Software Program was used to analyze the data collected as well as write study reports. The results show that sustainable village development has led to the development of social, economic, and environmental resilience, which has an impact on deurbanization. Ruralization also occurred, where people living in the city moved to villages for economic, social, and cultural reasons, especially those who have kinship relations. In conclusion, private sector contributions can improve rural areas, because professional workers from cities move to villages to work in private companies, thereby supporting rural economic growth.

Role of Urinary Matrix Metalloproteinase-7 (MMP-7) as an Early Marker of Renal Dysfunction in Diabetic Individuals: A Cross-Sectional Study.

The matrix metalloproteinase 7(MMP-7) level gets heightened in the urine samples of diabetic individuals with impaired renal function. Renal biopsy is seldom offered because of its invasive nature. These concerns spurred the investigation of relationships between urine MMP-7 levels and the renal function of diabetic individuals. Studies exploring this aspect are scarce. We aimed to evaluate the glycemic and renal parameters of female and male individuals with or without type 2 diabetes mellitus (T2DM) or kidney disease. We also assessed the correlation of urine MMP-7 with various parameters. This prospective, analytical, cross-sectional study was conducted at Kalinga Institute of Medical Sciences (KIMS), Bhubaneswar, India, from February 2020 to January 2023. Female and male individuals 18-85 years of age diagnosed with either T2DM, hypertension, or kidney disease were assessed for their glycemic indices and renal parameters. Those with both renal disease and T2DMwere placed in group A. The diabetic individuals without kidney disease constituted group B. People in group C had neither kidney disease nor T2DM. Patients in group D had kidney disease but were not diabetics. The parameters of the male and female participants in each of the four groups were assessed and compared, including: age, body mass index (BMI), fasting blood sugar (FBS), glycosylated hemoglobin (HbA1c), serum urea, serum creatinine, estimated glomerular filtration rate (eGFR), urine albumin, urine creatinine, urine albumin-creatinine ratio (ACR), serum sodium, serum potassium, and urine MMP-7 levels. Furthermore, we correlated urine MMP-7 with all these traits. We used R software (version 4.4.0, Vienna, Austria) for data analysis. Two hundred eighty-seven (87.5%) of the 328 individuals we screened were eligible. Of them, group A had the maximum number (94) of participants, followed by B (75), C (65), and D (53). Males comprised 60.3% (n = 173) of the study population. The median age of the participants was 52.0 (44.0-61.1) years. The intergroup variations were statistically significant (p < 0.001) owing to their glycemic status and renal function. The gender-basis comparison of FBS and HbA1c yielded non-significant differences. On the contrary, assessment of the renal parameters revealed significant differences (p < 0.001) between females and males. The study population had a median urine MMP-7 level of 19.9 (1.1-50.5) µg/L. Significant associations with urine MMP-7 were found with serum creatinine (r = 0.91, p < 0.001), urine ACR (r = 0.86, p < 0.001), and eGFR (r = -0.84, p < 0.001). Our study portrayed that male diabetics, in comparison to female diabetics, had greater levels of urine ACR, urine MMP-7, eGFR, and serum creatinine. Moreover, urine ACR, eGFR, and serum creatinine strongly correlated with the urine MMP-7 level.

COVID-19 and lifelong learning: older adult peer educators’ perspective on the pandemic’s effect on adult education

ABSTRACT Background The COVID-19 pandemic ushered in a period of unprecedented uncertainty, profoundly affecting societies worldwide. Older adults often faced heightened risks of isolation and health complications. As research in the aftermath of the pandemic has sought to understand its multifaceted impacts, there remains a notable gap in examining older adults’ access to education, particularly within the Lifelong Learning Institutes (LLIs) or Universities of the Third Age (U3A). Methodology In the course of a broader study focusing on older adult peer educators, the topic of COVID-19 emerged as a prominent and recurring theme of 14 interviews with US-based peer educators. Using a qualitative content analysis approach supported by WebQDA (Qualitative Data Analysis Software) we identified key themes and subthemes in the interview data. Findings Major themes included the impact of COVID-19 in the classroom and institution and also in the personal lives of the students and educators. A prominent subtheme was the introduction, or shift, in technology. Technology was seen as a powerful tool for expanding educational opportunities for older adults and engaging a broader audience. The resilience and adaptability of educators in navigating the challenges posed by the pandemic were also frequently discussed. Conclusion This study highlights the way in which the COVID-19 pandemic has reshaped education within Lifelong Learning Institutes. The findings underscore the importance of addressing the specific needs and challenges faced by older adult peer educators and highlight the opportunities for enhancing specific person-based support and allocating resources effectively in the evolving post-pandemic educational landscape.

Unveiling the determinant factors of go club program loyalty in a super application

This research aimed to analyze the factors affecting super application brand loyalty with the emergence of digital loyalty programs in Indonesia. A strong super-application has gained popularity and sustained customer demand due to Indonesia's smartphone industry expansion. To achieve this objective, a quantitative-qualitative approach utilizing Structured Equation Modeling (SEM) and interviews was employed. Ten-fold indicators determined the sample size, while convenience sampling gathered 392 respondents. The software for data analysis is SmartPLS 4.1.0.0. The results indicate the acceptance of eight hypotheses and the rejection of the remaining two. Playfulness is positively affecting attitudes and loyalty program usage. Next, affective commitment positively affects attitude and loyalty program usage. Next, reward attractiveness positively affects attitude. Finally, the relationship between attitude, usage, satisfaction, and loyalty is significant. The determinant factors of brand loyalty were playfulness, reward attractiveness, and affective commitment. The theoretical contribution is that the impact of loyalty programs on brand loyalty reveals that factors like playfulness and affective commitment influence attitudes and usage, despite gamification's potential moderating effect. The practical implication is that Gojek should improve its loyalty program strategy by diversifying the range of rewards and integrating gamification, particularly in-app games, to maintain user engagement and brand loyalty.

A robust paradigm for studying regeneration after traumatic spinal cord injury in zebrafish

BackgroundZebrafish are vertebrates with a high potential of regeneration after injury in the central nervous system. Therefore, they have emerged as a useful model system for studying traumatic spinal cord injuries. New MethodUsing larval zebrafish, we have developed a robust paradigm to model the effects of anterior spinal cord injury, which correspond to the debilitating injuries of the cervical and thoracic regions in humans. Our new paradigm consists of a more anterior injury location compared to previous studies, a modified behavioral assessment using the visual motor response, and a new data analysis code. ResultsOur approach enables a spinal cord injury closer to the hindbrain with more functional impact compared to previous studies using a more posterior injury location. Results reported in this work reveal recovery over seven days following spinal cord injury. Comparing with existing MethodsThe present work describes a modified paradigm for the in vivo study of spinal cord regeneration after injury using larval zebrafish, including an anterior injury location, a robust behavioral assessment, and a new data analysis software. ConclusionsOur findings lay the foundation for applying this paradigm to study the effects of drugs, nutrition, and other treatments to improve the regeneration process.

Do school Water, Sanitation, and Hygiene facilities affect students' health status, attendance, and educational achievements? A qualitative study in Nepal.

Access to safe and sufficient drinking Water, Sanitation, and good Hygiene (WASH) facilities in schools play a crucial role in preventing students from numerous Neglected Tropical Diseases, improving the learning environment in schools, and creating resilient communities living in a healthy environment. This study aims to explore the impact of combining WASH facilities on students' health status, school attendance, and educational achievements. Four schools, two with improved and two without improved WASH facilities, were selected purposively from Dhanusha and Chitwan districts of Nepal. A total of 24 participants, 16 students, and eight teachers were also purposively selected based on the Theory of Data Saturation. The participants were interviewed face-to-face using study guidelines; Key Informants Interview for teachers and In-depth Interview for students. The data were audio recorded and analyzed thematically using Dedoose 9.0.17 qualitative data management and analysis software. School WASH facilities have a significant impact on students' health and well-being. Poor school-WASH facilities hindered students' school attendance, particularly for menstruating girls. School without separate toilets for girls, including menstruation hygiene facilities, lack of water and soap, sanitary pad, and secure toilet's door often have higher rates of absenteeism among girls. Poor teacher and students' relationships, students' low interest in education, household chores, and participation in social customs also contribute to students' absence from school and low educational performance. It is important to note that inadequate WASH facilities affect not only students, but also teachers in the same school. The lack of safe and sufficient drinking water, unimproved sanitation, and poor hygiene facilities were seen by students and teachers as reducing their health and well-being, school attendance, and academic performance. Thus, schools need prioritize and promote the provision of improved WASH facilities for the betterment of students' health, attendance, and educational proficiency.

“It is something you live with, like an organ in your body” a qualitative study on the lived experiences of people suffering from chronic low back pain in Lebanon

Purpose This paper aims to understand the distinctive biopsychosocial aspects and patient perspectives on chronic low back pain in Lebanon, an Arab country with a unique and rich cultural heritage. Method Qualitative, semi-structured interviews with 12 Lebanese patients purposefully sampled from various governorates. The interviews included participants from different geographic areas and religions. The data underwent analysis through an inductive thematic approach guided by a bounded relativist ontology, a subjectivist epistemology, and a descriptive phenomenological framework. The coding process was managed by computer-assisted qualitative data analysis software (QSR NVivo version 12.0). Results The researchers identified and constructed two themes: (1) Chronic low back pain: understanding the impact, coping strategies, and communication patterns in lived experiences within the Lebanese context. This theme sheds light on the complexities of pain management and societal influences in Lebanon. (2) Explanatory model of patients living with chronic low back pain in Lebanon. This theme allowed an exploration of the multifaceted narratives of chronic low back pain. Conclusion This study found that Lebanese individuals attribute chronic low back pain to biomedical factors despite some recognizing psychosocial elements. It emphasizes the need to educate patients on the biopsychosocial model, facilitate better care, and dispel misconceptions.

Refractive errors and the uniform patient fee scheme at a public hospital in South Africa

Background: Uniform Patient Fee Scheme (UPFS) refers to the healthcare subsidy levels provided by public hospitals in South Africa. Such subsidies indirectly reflect socio-economic factors and thus potentially might impact upon distributions of refractive error.Aim: To investigate refractive errors based on the UPFS-classified records of patients consulted at an Optometry Clinic between January 2018 and December 2019. This will provide frequencies and other measures, possibly providing preliminary estimates of prevalences for the wider population for the region concerned.Setting: The study was conducted at Sekororo Hospital in Limpopo province.Methods: Data for UPFS and refractive errors (via subjective refraction) were collected retrospectively based on the archived clinical records. Statistics and Data Analysis (Stata) software was used to analyse data.Results: For H0 in the right eyes means (± s.d.) for myopia, hyperopia, and astigmatism were −2.04 ± 2.60, 1.38 ± 1.72, and −1.07 ± 0.64, respectively. For H0 (left eyes): Myopia (−2.04 ± 2.09), hyperopia (1.47 ± 1.73), and astigmatism (−1.04 ± 0.64). For H1 (right eyes): Myopia (−1.79 ± 1.50), hyperopia (1.06 ± 0.72), and astigmatism (−1.14 ± 0.81). For H1 (left eyes): myopia (−1.71 ± 1.46), hyperopia (1.24 ± 0.91), and astigmatism (−1.71 ± 0.74). (No records were found for H2, H3, or private patients.)Conclusion: Hyperopia and astigmatism were the most common in H0 records while myopia was the most common in H1.Contribution: Various authorities and others in South Africa might use this data and results for National Health Insurance planning policies and implementation purposes.

MuscleX: data analysis software for fiber diffraction patterns from muscle.

MuscleX is an integrated, open-source computer software suite for data reduction of X-ray fiber diffraction patterns from striated muscle and other fibrous systems. It is written in Python and runs on Linux, Microsoft Windows or macOS. Most modules can be run either from a graphical user interface or in a `headless mode' from the command line, suitable for incorporation into beamline control systems. Here, we provide an overview of the general structure of the MuscleX software package and describe the specific features of the individual modules as well as examples of applications.

Symposium 1: Tracing analytic assemblages – doing doctoral research with actor-network theory

The practices of doctoral education are intricately entangled with technologies. This methodological paper examines the practical concerns involved in doing the analytic work in a networked learning setting with Actor-Network theory (ANT). It is a story about engaging with ANT as a companion in an ethnographic research project on teaching practices in Sweden during the Covid-19 pandemic. The empirical examples are pulled from online interviews in the pandemic outbreak and two ways of assembling the analytic practices of those interviews. On the premises that method and technology are non-neutral, the focus is on how the interviews are analysed and the modes of knowing that they form. For example, the paper examines how computer-assisted qualitative data analysis software acts on the analyses of the interviews and the knowledge patterns made possible and what signals are silenced. A second analytic assemblage is deployed that traces those signals. Based on the empirical examples of doing analyses, the paper discusses how analytic assemblages change and move research and the researcher in unpredictive and performative ways that troubles the expectations of a singularised doctoral journey.

Understanding Higher-Order Interactions in Information Space.

Methods used in topological data analysis naturally capture higher-order interactions in point cloud data embedded in a metric space. This methodology was recently extended to data living in an information space, by which we mean a space measured with an information theoretical distance. One such setting is a finite collection of discrete probability distributions embedded in the probability simplex measured with the relative entropy (Kullback-Leibler divergence). More generally, one can work with a Bregman divergence parameterized by a different notion of entropy. While theoretical algorithms exist for this setup, there is a paucity of implementations for exploring and comparing geometric-topological properties of various information spaces. The interest of this work is therefore twofold. First, we propose the first robust algorithms and software for geometric and topological data analysis in information space. Perhaps surprisingly, despite working with Bregman divergences, our design reuses robust libraries for the Euclidean case. Second, using the new software, we take the first steps towards understanding the geometric-topological structure of these spaces. In particular, we compare them with the more familiar spaces equipped with the Euclidean and Fisher metrics.

UKB.COVID19: an R package for UK Biobank COVID-19 data processing and analysis

COVID-19 caused by SARS-CoV-2 has resulted in a global pandemic with a rapidly developing global health and economic crisis. Variations in the disease have been observed and have been associated with the genomic sequence of either the human host or the pathogen. Worldwide scientists scrambled initially to recruit patient cohorts to try and identify risk factors. A resource that presented itself early on was the UK Biobank (UKBB), which is investigating the respective contributions of genetic predisposition and environmental exposure to the development of disease. To enable COVID-19 studies, UKBB is now receiving COVID-19 test data for their participants every two weeks. In addition, UKBB is delivering more frequent updates of death and hospital inpatient data (including critical care admissions) on the UKBB Data Portal. This frequently changing dataset requires a tool that can rapidly process and analyse up-to-date data. We developed an R package specifically for the UKBB COVID-19 data, which summarises COVID-19 test results, performs association tests between COVID-19 susceptibility/severity and potential risk factors such as age, sex, blood type, comorbidities and generates input files for genome-wide association studies (GWAS). By applying the R package to data released in April 2021, we found that age, body mass index, socioeconomic status and smoking are positively associated with COVID-19 susceptibility, severity, and mortality. Males are at a higher risk of COVID-19 infection than females. People staying in aged care homes have a higher chance of being exposed to SARS-CoV-2. By performing GWAS, we replicated the 3p21.31 genetic finding for COVID-19 susceptibility and severity. The ability to iteratively perform such analyses is highly relevant since the UKBB data is updated frequently. As a caveat, users must arrange their own access to the UKBB data to use the R package.

Efforts to Increase Motivation to Read Recount Text Through Playing Games for Elementary School Children at SDN Koli

Background. Traditional methods of teaching recount texts often struggle to engage students effectively. Educational games offer a potential solution to increase motivation and comprehension in language learning, particularly for primary school students. Purpose. This research aims to investigate the effectiveness of educational games in increasing motivation to read recount texts among students at SDN Koli. Method. The study employs a qualitative approach, utilizing QDA Miner software for data analysis. Data collection methods include in-depth interviews, participant observation, and document analysis of classroom teaching and learning activities. The research focuses on exploring students' and teachers' experiences, perceptions, and motivations regarding the use of games in learning. Results. The findings indicate that educational games significantly increase student motivation and engagement in learning recount texts. These games make the learning process more exciting and interactive, helping students better understand story structure and event sequences. In the affective domain, games foster reflection and humility, creating a positive learning environment. Cognitively, the games prove highly effective in improving writing skills and contribute significantly to reading and speaking abilities. While the psychomotor impact is smaller, the games still help students manage emotions and maintain focus. Conclusion. The integration of educational games in teaching recount texts not only enhances cognitive skills but also positively impacts students' affective and psychomotor aspects. This research underscores the importance of innovative learning methods in meeting students' needs in the digital era. By adopting such approaches, educators can nurture a generation of students who are more motivated, skilled, and prepared for future challenges in language learning and beyond.

Exploring Ion Mobility Mass Spectrometry Data File Conversions to Leverage Existing Tools and Enable New Workflows.

Ion mobility (IM) is often combined with LC-MS experiments to provide an additional dimension of separation for complex sample analysis. While highly complex samples are better characterized by the full dimensionality of LC-IM-MS experiments to uncover new information, downstream data analysis workflows are often not equipped to properly mine the additional IM dimension. For many samples the data acquisition benefits of including IM separations are all that is necessary to uncover sample information and the full dimensionality of the data is not required for data analysis. Postacquisition reduction and adaptation of the dimensions of LC-IM-MS and IM-MS experiments into an LC-MS format opens the possibility to use a plethora of existing software tools. In this work, we developed data file conversion tools to reduce the complexity of IM data analysis. Three data file transformations are introduced in the PNNL PreProcessor software: (1) mapping the IM axis to the LC axis for IM-MS data, (2) converting the drift time vs m/z space to CCS/z vs m/z space, and (3) transforming All Ions IM/MS mobility aligned fragmentation data to a standard LC-MS DDA data file format. These new data file conversions are demonstrated with corresponding lipidomics and proteomics workflows that leverage existing LC-MS data analysis software to highlight the benefits of the data transformations.

Inter-Coder Agreement in Qualitative Coding: Considerations for its Use

&lt;i&gt;The historically quantitative-dominated field of health sciences has increasingly embraced qualitative methods. However, calls for quantitative measures of rigor, such as Inter-coder Agreement (ICA), remain. The aim of this manuscript is to demystify ICA and provide practical guidance. I begin by describing considerations while planning for ICA, including differences between various ICA tests (i.e., percent agreement, Holsti Method, Cohen’s kappa, Krippendorf’s alpha, and Gwet’s AC1 and AC2), setting the threshold of acceptability for your chosen test, deciding whether to use qualitative data analysis software, choosing the number of coders, selecting what data will be coded by more than one coder, developing a deductive codebook, creating a process for resolving coding disagreements, and establishing an audit trail for codebook changes. Next, I provide step-by-step guidance on an iterative process used for enacting ICA. Finally, I discuss the importance of reporting, emphasizing clarity, conciseness, completeness, and accuracy.&lt;/i&gt;

What Is Qualitative Research? An Overview and Guidelines

This guide explains the focus, rigor, and relevance of qualitative research, highlighting its role in dissecting complex social phenomena and providing in-depth, human-centered insights. The guide also examines the rationale for employing qualitative methods, underscoring their critical importance. An exploration of the methodology’s strengths, such as its ability to offer contextual depth and holistic perspectives, is juxtaposed against challenges like constrained generalizability and potential researcher bias, accompanied by practical mitigation strategies. Covering a spectrum of qualitative approaches, including grounded theory, phenomenology, ethnography, action research, and general inquiry, the guide sheds light on diverse data collection and analysis techniques. Noteworthily, the guide underscores the crucial aspect of trustworthiness in qualitative research, detailing methods to establish credibility, dependability, confirmability, and transferability. The integration of technologies like recording and transcribing tools with data analysis software and the growing influence of artificial intelligence, machine learning, and deep learning are also explored. Concluding with a discussion on ethical considerations, from participant recruitment to data stewardship, this guide serves as an essential resource that offers insightful, actionable guidance for conducting effective and impactful qualitative research.

PyFMLab: Open-source software for atomic force microscopy microrheology data analysis

Background Atomic force microscopy (AFM) is one of the main techniques used to characterize the mechanical properties of soft biological samples and biomaterials at the nanoscale. Despite efforts made by the AFM community to promote open-source data analysis tools, standardization continues to be a significant concern in a field that requires common analysis procedures. AFM-based mechanical measurements involve applying a controlled force to the sample and measure the resulting deformation in the so-called force-distance curves. These may include simple approach and retract or oscillatory cycles at various frequencies (microrheology). To extract quantitative parameters, such as the elastic modulus, from these measurements, AFM measurements are processed using data analysis software. Although open tools exist and allow obtaining the mechanical properties of the sample, most of them only include standard elastic models and do not allow the processing of microrheology data. In this work, we have developed an open-source software package (called PyFMLab, as of python force microscopy laboratory) capable of determining the viscoelastic properties of samples from both conventional force-distance curves and microrheology measurements. Methods PyFMLab has been written in Python, which provides an accessible syntax and sufficient computational efficiency. The software features were divided into separate, self-contained libraries to enhance code organization and modularity and to improve readability, maintainability, testability, and reusability. To validate PyFMLab, two AFM datasets, one composed of simple force curves and another including oscillatory measurements, were collected on HeLa cells. Results The viscoelastic parameters obtained on the two datasets analysed using PyFMLab were validated against data processing proprietary software and against validated MATLAB routines developed before obtaining equivalent results. Conclusions Its open-source nature and versatility makes PyFMLab an open-source solution that paves the way for standardized viscoelastic characterization of biological samples from both force-distance curves and microrheology measurements.

Explaining the process of learning about dignity by undergraduate nursing students: A grounded theory study.

The learning process about dignity and how undergraduate nursing students experience and use this ethical knowledge is an under-represented field in nursing research. To overcome the lack of conceptual clarity, it is important to understand what processes and dimensions students develop to support this learning outcome. This study aimed to explain the process of learning about dignity by undergraduate nursing students. A qualitative study was conducted using the grounded theory method. Data was collected through free reports and in-depth semi-structured interviews with 20 participants. A focus group was held for the selective coding. Sampling began purposefully and evolved into theoretical. Reflective and theoretical memos were generated from the data collection and constant comparison. Data analysis was performed using qualitative data analysis software using Corbin and Strauss' method. The research was approved by a specialized research ethics committee from a Health School. The process of learning about dignity by undergraduate nursing students revealed 'recognition of dignity' as the core category, supported by five main categories: 'proto-conscience of dignity', 'pathway to nursing', 'consciousness of dignity', 'ways of learning', and 'becoming capable'. These categories illustrate the processes and dimensions involved in nursing students' concept translation of dignity learning, allowing a theory to emerge. The 'Recognition of Dignity' theory aims to contribute to developing educational, training, and supervision processes for nursing programs. It seeks to enhance the ethical and moral development of undergraduate nursing students by helping them understand the concept of dignity and its fundamental importance in nursing.

The potential of lesson study in enhancing secondary school mathematics teachers’ pedagogical practices in lesson planning: evidence from Ethiopia

PurposeThe main purpose of this study was to explore how engaging in lesson study enhances secondary school mathematics teachers’ pedagogical practice in lesson planning in Jimma, Ethiopia.Design/methodology/approachThe study employed a design-based research approach with qualitative and quantitative data collected from two secondary schools, and 12 mathematics teachers. A purposive sampling technique was used to select participants. Interviews, observations, questionnaires and document analysis were the main sources of data. Qualitative data were analyzed using themes with the support of Atlas-ti qualitative data analysis software. Quantitative data were analyzed using the Wilcoxon ranked signs test.FindingsThe findings revealed that engaging secondary school mathematics teachers in lesson study enhanced their lesson planning competence. As a result, teachers began to carefully plan detailed lessons, use curriculum materials and create more student-oriented lessons. Lesson study was found to be a potent model on which to build secondary school mathematics teachers’ lesson planning competence. Hence, it would be rewarding to integrate lesson study into the present school-based teachers’ pedagogical capacity-building program in the study settings.Research limitations/implicationsThe data were collected from particular localities with a small sample size in the quantitative phase. Therefore, it is difficult to generalize to the entire secondary school teachers in the country. However, thick descriptions were provided that would allow readers to determine the transferability of the findings to their specific school context. Future research should investigate the effects that enhanced TPP in lesson planning has on teachers’ mathematics teaching in more schools using a larger sample size.Practical implicationsThis study provides insight into and empirical evidence of how engaging in the process of LS is essential to enhance teachers’ lesson planning competence. It adds important knowledge to a small but growing model of lesson study research. It also informs future researchers in the practical use of LS where lesson planning is a crucial concern in many secondary schools of the country.Originality/valueThis research was originally conducted to build mathematics teachers' pedagogical practice in lesson planning through lesson study in Ethiopian secondary school contexts.

Diagnostic Performance of TOF, 4D MRA, Arterial Spin-Labeling, and Susceptibility-Weighted Angiography Sequences in the Post-Radiosurgery Monitoring of Brain AVMs.

Brain AVMs are congenital anomalies of the cerebrovascular system, often discovered incidentally or through symptomatic presentations such as intracranial hemorrhage, seizure, headache, or neurologic deficits. Various treatment modalities exist for AVMs, including radiosurgery, a treatment technique that is noninvasive and efficient. Accurate imaging is crucial for risk assessment, treatment planning, and monitoring of these patients before and after radiosurgery. Currently, DSA is the preferred imaging technique. Despite its efficacy, DSA is notably invasive, presenting inherent risks to the patients. This systematic review and meta-analysis aimed to evaluate the efficacy of MRI sequences for monitoring brain AVMs after radiosurgery. We performed a comprehensive search of PubMed, Scopus, Web of Science, and EMBASE databases and a methodologic quality assessment with the QUADAS-2 checklist diagnostic test accuracy. According to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, 3,220 abstracts were screened, 98 articles were reviewed in full text, and 14 articles met the inclusion criteria. We used the bivariate random-effects meta-analysis model with STATA/MP 17 software for data analysis. No publication bias was detected. Fourteen studies were eligible for qualitative and quantitative analysis. MRI offers high sensitivity (85%) and specificity (99%) in detecting residual AVMs. Different MRI sequences, including 3D TOF-MRA, 4D MRA, and arterial spin-labeling (ASL) demonstrated varying diagnostic accuracies with areas under the curve of 0.92, 0.97, and 0.96, respectively. 4D MRA had a sensitivity of 72% and specificity of 99%, ASL showed a sensitivity of 90% and specificity of 92%, while 3D TOF-MRA had 90% sensitivity and 87% specificity. Meta-regression did not fully explain the sources of heterogeneity. Only 1 study assessed the susceptibility-weighted angiography (SWAN) method, and most studies involved small participant groups with varied MR techniques and sequences. Additionally, the retrospective nature of most studies may introduce bias, warranting cautious interpretation of the results. MRI sequences show acceptable diagnostic performance in postradiosurgery monitoring of brain AVMs, with ASL and 4D MRA showing acceptable diagnostic accuracy. Combining different MRI sequences may further enhance diagnostic reliability. However, further investigation is needed to assess whether MRI sequences can serve as a feasible substitute for DSA, considering their risk-benefit profile, with the potential to establish them as the recommended standard.