Analysis Approach Research Articles

Identifying the contributors to nursing caring success stories.

To (a) seek examples of nursing caring success stories and (b) identify the common contributors to these successes. By focusing on the successes of nursing care rather than critically examining failures, this research seeks to provide examples of proven and feasible approaches and processes for improving care. This study used a narrative inquiry design. Data were collected through group interviews. Four interviews were conducted with a total of 20 nurse participants working in inpatient settings in South Australian hospitals. A thematic analysis approach was used to analyse the data. Two dominant themes concerning the contributors to caring success were identified. These contributors were (1) the provision of holistic care and (2) the influence of the caring community, which includes family members and other patients. The findings also indicated that the definition of caring success according to nurses is not aligned with organisational performance indicators but is more closely represented by caring values. Success, according to nurses, is not exclusively defined by patient outcomes but includes the approach to, and process of, care delivery. Nurses value the caring process while working in an environment that primarily values clinical and systems-level outcomes. Nurses want patients and their families, allied health professionals and hospital executives to be involved and invested in the process of care. This study addressed a gap in the current literature to identify commonalities in nursing success stories, the contributors informing these successes and how these contributors can facilitate improved patient care. Understanding nursing definitions of caring success provides an opportunity to expand upon current accepted industry definitions and perspectives such as key performance indicators. Consolidated Criteria for Reporting Qualitative Research (COREQ) checklist. No direct patient or public contribution.

Relationship between sense of coherence and depression, a network analysis

AbstractThe “sense of coherence” incorporates the notion that when life seems comprehensive, manageable, and meaningful for an individual, even under tremendous adversity, this accounts for stamina and confidence. Its absence is associated with mental health problems, including depression. The current analysis aimed to explore the relationship between the sense of coherence and depression through a network analysis approach in a sample of 181 people with depression. The mean age of the individuals in the sample was 35.59 (11.50) years, and 76.8% were females (n = 139). All participants had at least one previous depressive episode; the duration of the current episode was 30.30 (77.30) days. Sense of coherence was assessed using the 13-item Sense of Coherence Scale (SOC-13). The severity of depression was quantified with the Beck Depression Inventory (BDI-I). The correlations between the two scales, three networks (i.e., SOC-13; BDI-I and joint SOC-13/BDI-I), and their centrality indices were calculated. The mean SOC-13 was 40.56 ± 9.99, and the mean BDI-I was 49.90 ± 9.26. There was a strong correlation-concordance (− 0.65; 95% CI: − 0.72 to − 0.55) index between the two scales. We identified detailed relationship dynamics between symptoms, clusters, and domains through the novel network analysis approach. The analysis of SOC-13 nodes revealed the pivotal role of social relationships in the network. However, in the depression network, we found a role for affection (in contrast to neglect) and joy (as opposed to boredom). In conclusion, solid and sustainable personal relationships in distress and adversity stand against the burden of depression.

The Effect of Big Data Analytics on Predictive Policing: The Mediation Role of Crisis Management

Objective: The objective of this study is to evaluate the impact of big data analytics (BDA) on predictive policing, particularly examining the mediating role of crisis management in this relationship. Theoretical Framework: The research is anchored in the domain of big data analytics, focusing on its application within law enforcement for enhancing predictive policing capabilities. The study explores how crisis management serves as a linkage between data analytics and predictive policing practices. Method: The study gathered data from 450 individuals working across various police departments in Dubai, utilizing a questionnaire to collect responses. The analytical approach was based on Structural Equation Modeling, conducted using AMOS software. Results and Discussion: Findings from the research indicate that big data analytics significantly boosts predictive policing and crisis management. Importantly, crisis management was identified as a mediating factor between big data analytics and its efficacy in predictive policing. These results suggest that big data analytics not only directly enhances predictive policing but also improves it indirectly through effective crisis management. Research Implications: This study underscores the importance of integrating big data analytics into police operations to advance predictive policing capabilities. It highlights the dual benefits of big data analytics in both direct application and enhancement through crisis management processes. Originality/Value: This research contributes to the limited but growing body of literature on the application of big data analytics in predictive policing. It offers practical guidelines for police forces, especially within the UAE, to better harness big data for improving their operational effectiveness and crisis management strategies. The study also discusses broader implications for both practice and ongoing research in this evolving field.

Enhancing missing persons search strategies through technological touchpoints

ABSTRACT The search for the missing persons is a top priority for police, and technology is playing an increasingly important role in increasing the accuracy and rigour of these investigations. This study aims to increase understanding of police decision-making in the missing persons search process and to examine the desired point and level of technology participation from the user's perspective. Three empirical studies and workshops were conducted with police, UX researchers, and computer science researchers. During the workshops, participants developed diagrams to represent police work methods and difficulties and discussed how to identify optimal touch points for technology integration. The findings revealed that the uncertainty of information is the biggest challenge in missing persons search, and that closed-circuit television (CCTV) is a valuable tool. A comparative experiment was conducted to compare the CCTV utilisation investigation strategies of police experts and novices. Findings showed that experts are more efficient and effective in using CCTV to search for missing persons. Experts used their experiential knowledge to interpret information and judge the reliability of information more accurately than novices. Additionally, novices used strategies through rapid repetition of trial and error, while experts made decisions based on experience and intuition, but pursued decision-making based on explicit information. The study concludes by discussing technological approaches for information identification, analysis, and labour replacement in missing person investigations. Such approaches could help overcome the challenge of uncertainty and improve the overall efficiency and effectiveness of these investigations.

Data-Driven Identification and Analysis of Waiting Times in Business Processes

AbstractReducing waiting times in end-to-end business processes is a recurrent concern in the field of business process management. The uptake of data-driven approaches in this field in the past two decades, most notably process mining, has created new opportunities for fine-grained analysis of waiting times based on execution data. As a result, a wide range of approaches for waiting time identification and analysis on the basis of business process execution data have been reported in the literature. In many instances, different approaches have considered different notions of waiting time and different causes for waiting time. At present, there is a lack of a consolidated overview of these manifold approaches, and how they relate to or complement each other. The article presents a literature review that starts with the question of what approaches for identification and analysis of waiting time are available in the literature, and then refines this question by adding questions which shed light onto different causes and notions of waiting time. The survey leads to a multidimensional taxonomy of data-driven waiting time analysis techniques, in terms of purpose, causes, and measures. The survey identifies gaps in the field, chiefly a scarcity of integrated multi-causal approaches to analyze waiting times in business processes, and a lack of empirically validated approaches in the field.

Analyzing the efficacy of comprehensive testing: a comprehensive evaluation

This study aimed to examine the variations in comprehensive exam results in the English department at Qassim University in Saudi Arabia across six semesters, focusing on average score, range, and standard deviation, as well as overall student achievements. Additionally, it sought to assess the performance levels of male and female students in comprehensive tests and determine how they differ over the past six semesters. The research design utilized both analytical and descriptive approaches, with quantitative analysis of the data using frequency statistics such as mean, standard deviation, and range. The data consisted of scores from six consecutive exit exams. The findings reveal that male students scored slightly higher on average than female students, with minimal difference (p = 0.07). Moreover, male scores exhibited more variability and spread, indicating varying performance levels. These results suggest the need for further investigation into the factors that contribute to gender-based differences in test performance. Furthermore, longitudinal studies tracking individual student performance over multiple semesters could offer a more in-depth understanding of academic progress and the efficacy of comprehensive exam practices.

Dinamismo e identificación de participantes en la construcción discursiva de la nación estadounidense

This article analyzes the linguistic choices used in political discourse to represent social actors and their role in the construction of national storylines. We focus on Donald Trump’s and Joseph Biden’s inaugural speeches as a critical exploratory context. The analytical approach involves contrasting their choices for assigning dynamism to socialactors through transitivity roles and for identifying participants through direct, indirect, and pronominal strategies. Our findings show that Trump assigns Actor + Goal roles that construe citizens as agents impinging on material reality, while Biden assigns them Actor – Goal roles that represent citizens as participants in happenings. Trump’s identification of participants shows a higher proportion of indirect strategies linked with possessivequalification, whereas Biden stands out for his frequent use of the singular first person. The findings suggest connections between the strategies identified and the construction of national identities and storylines, both permeated by political leaders’ ideological orientations.

Serum bile acid and unsaturated fatty acid profiles of non-alcoholic fatty liver disease in type 2 diabetic patients.

The understanding of bile acid (BA) and unsaturated fatty acid (UFA) profiles, as well as their dysregulation, remains elusive in individuals with type 2 diabetes mellitus (T2DM) coexisting with non-alcoholic fatty liver disease (NAFLD). Investigating these metabolites could offer valuable insights into the pathophy-siology of NAFLD in T2DM. To identify potential metabolite biomarkers capable of distinguishing between NAFLD and T2DM. A training model was developed involving 399 participants, comprising 113 healthy controls (HCs), 134 individuals with T2DM without NAFLD, and 152 individuals with T2DM and NAFLD. External validation encompassed 172 participants. NAFLD patients were divided based on liver fibrosis scores. The analytical approach employed univariate testing, orthogonal partial least squares-discriminant analysis, logistic regression, receiver operating characteristic curve analysis, and decision curve analysis to pinpoint and assess the diagnostic value of serum biomarkers. Compared to HCs, both T2DM and NAFLD groups exhibited diminished levels of specific BAs. In UFAs, particular acids exhibited a positive correlation with NAFLD risk in T2DM, while the ω-6:ω-3 UFA ratio demonstrated a negative correlation. Levels of α-linolenic acid and γ-linolenic acid were linked to significant liver fibrosis in NAFLD. The validation cohort substantiated the predictive efficacy of these biomarkers for assessing NAFLD risk in T2DM patients. This study underscores the connection between altered BA and UFA profiles and the presence of NAFLD in individuals with T2DM, proposing their potential as biomarkers in the pathogenesis of NAFLD.

Consistent Robust Analytical Approach for Outlier Detection in Multivariate Data using Isolation Forest and Local Outlier Factor

Outlier detection in real-time from multivariate streaming data is an important research subject in numerous areas. The new presentation of gradual Neighborhood Anomaly Variable (iLOF) and its variations has acquired consideration for their high recognition execution in information streams with evolving circulations. This paper presents a new intelligent exception location framework called include rich intelligent anomaly discovery, which integrates human interaction into the detection process to improve performance and simplify detection. It offers interactive mechanism that allows for instinctive client cooperation during every vital stage of the fundamental anomaly recognition calculation, for example, thick cell choice, area mindful distance thresholding, and last top exception approval. This approach helps resolve the challenge of specifying key parameters like density and distance thresholds in other outlier detection methods. Additionally, the system proposes an innovative optimization method to enhance grid-based space partitioning. The Local Outlier Factor (LOF) measures the level of outlierness of each occasion in light of the conveyance thickness in the dataset. Higher LOF values indicate a higher likelihood of an instance being an outlier. Instances with LOF values above a set threshold are identified as outliers. The calculation of LOF values involves several steps, which are detailed in original articles for further reference.

Causal relationship of interleukin-6 and its receptor on sarcopenia traits using mendelian randomization

BackgroundPrevious research has extensively examined the role of interleukin 6 (IL-6) in sarcopenia. However, the presence of a causal relationship between IL-6, its receptor (IL-6R), and sarcopenia remains unclear.MethodIn this study, we utilized summary-level data from genome-wide association studies (GWAS) focused on appendicular lean mass (ALM), hand grip strength, and walking pace. Single nucleotide polymorphisms (SNPs) were employed as genetic instruments for IL-6 and IL-6R to estimate the causal effect of sarcopenia traits. We adopted the Mendelian randomization (MR) approach to investigate these associations using the inverse variance weighted (IVW) method as the primary analytical approach. Additionally, we performed sensitivity analyses to validate the reliability of the MR results.ResultThis study revealed a significant negative association between main IL-6R and eQTL IL-6R on the left grip strength were − 0.013 (SE = 0.004, p < 0.001) and -0.029 (SE = 0.007, p < 0.001), respectively. While for the right grip strength, the estimates were − 0.011 (SE = 0.001, p < 0.001) and − 0.021 (SE = 0.008, p = 0.005). However, no evidence of an association for IL-6R with ALM and walking pace. In addition, IL-6 did not affect sarcopenia traits.ConclusionOur study findings suggest a negative association between IL-6R and hand grip strength. Additionally, targeting IL-6R may hold potential value as a therapeutic approach for the treatment of hand grip-related issues.

The mirror effect in online survey data: Evidence and implications for marketing theory and strategy

AbstractThis research reveals the presence, in online survey data, of a key pattern documented in psychology lab research: the Mirror Effect. The Mirror Effect occurs when unfamiliar stimuli are unexpectedly recognized as accurately as familiar stimuli, or more accurately. Using a set of familiar and unfamiliar words (as determined by lexical frequency), we first report that we can robustly replicate psychology lab research in an online survey, detecting the Mirror Effect. We then apply the same analytical approach to surveying consumer recognition of everyday brands (supermarkets, banks and car brands). We find that unfamiliar brands can be recognized with the same level of accuracy as familiar brands, and this effect is stronger than age and gender memory biases present in the data. However, we detect a boundary condition for branded apps, which are extremely unfamiliar brands competing in highly fragmented marketplaces, so very few get downloaded or used. For these digital brands, we find a Concordant Effect, as most respondents find it difficult to recognize highly unfamiliar branded apps (i.e., those with fewer than 5000 downloads). The Mirror Effect re‐emerges for highly experienced app users. These results demonstrate the implications of a generalizable empirical pattern from cognitive psychology for branding and advertising theory. The outcomes of this research also translate into practical guidelines for brand performance measurement via online surveys, mitigating recognition memory bias for the development of marketing strategies based on more accurate interpretation of empirical evidence.

Practice of breast self-examination and associated factors among women of reproductive age in the North Shoa Zone, Oromia, Ethiopia, 2022: a convergent mixed-methods study

ObjectiveTo assess practice of breast self-examination (BSE) and associated factors among women of reproductive age in the North Shoa Zone, Oromia, Ethiopia.DesignCommunity-based cross-sectional study with a convergent mixed-methods approach.SettingThe study...

Biological Sex, Gender Roles, and Sexual Scripts

This article examines how perception of male genital anatomy as specifically associated with the penis, and female genital anatomy associated with the vagina influences existing sexual scripts by prescribing vaginal penetration as basic form of sexual connection between female and male. Through a body-oriented and gender analysis approach, this study deconstructs how such anatomical perceptions reinforce gender roles and shape sexual behavior in both traditional (phallocentric) and egalitarian sexual scripts. The methodology employed in this article includes a comprehensive review of existing literature and qualitative analysis of data from various studies on sexual behavior and gender dynamics. This exploration contributes to a nuanced understanding of the complex interplay between anatomy, gender norms, and sexual behavior. Findings suggest that anatomical perceptions and gender roles significantly influence sexual expectations and behavior, perpetuating gender disparities even within attempts of more egalitarian sexual script.

Exploring the yield and yield contributing traits variability in dolichos bean (Lablab purpureus): A character association and path analysis approach

An experiment was conducted during 2019–20 and 2020–21 at ICAR-Central Institute for Subtropical Horticulture, Lucknow, Uttar Pradesh to evaluate the magnitude of variability in dolichos bean [Lablab purpureus (L.) Sweet] genotypes for important horticultural traits and their associations. The observed range and mean variations of the studied traits revealed a significant genetic diversity among the genotypes. The narrow gap in the genotypic (GCV) and the phenotypic coefficient of variation (PCV) for delineated characters indicated that they are governed by genetic factors, and environmental factors had little or no impact on the phenotypic expression of these traits. The traits including pod yield, days taken to first flowering, weight of pod, plant height, and pod width, showed positive GCV, indicating the presence of additive genes action. Traits such as pod weight, days taken to first flowering, and pod width displayed high heritability and moderate genetic advance, suggesting that the high heritability of these traits is due to the effects of additive genes and that genetic gain can be expected through the phenotypic selection. The higher genotypic correlations revealed an inherent association between the traits. Therefore, the selection criterion for high yield was proposed based on the strong character association between plant height, number of pods/cluster, pod width, and pod weight. The number of pods/plant, followed by the number of clusters/plant had the highest direct positive effect on yield. Consequently, pod yield may be increased through selection of heavier pods, more clusters/ plant, and more pods/cluster.

V4RIN: visual analysis of regional industry network with domain knowledge.

The regional industry network (RIN) is a type of financial network derived from industry networks that possess the capability to describe the connections between specific industries within a particular region. For most investors and financial analysts lacking extensive experience, the decision-support information provided by industry networks may be too vague. Conversely, RINs express more detailed and specific industry connections both within and outside the region. As RIN analysis is domain-specific and current financial network analysis tools are designed for generalized analytical tasks and cannot be directly applied to RINs, new visual analysis approaches are needed to enhance information exploration efficiency. In this study, we collaborated with domain experts and proposed V4RIN, an interactive visualization analysis system that integrates predefined domain knowledge and data processing methods to support users in uploading custom data. Through multiple views in the system panel, users can comprehensively explore the structure, geographical distribution, and spatiotemporal variations of the RIN. Two case studies were conducted and a set of expert interviews with five domain experts to validate the usability and reliability of our system.

How firm’s perception of economic policy uncertainty influences innovation quality

ABSTRACT Comprehending the consequences of firms’ perception of uncertainty is crucial in the context of a dynamic global economy. Based on a data set of China A-listed firms during 2007-2019, this paper constructs the indicator of firms’ perception of economic policy uncertainty (PEPU) through a textual analysis approach and examines its impact on the quality of firms’ innovation outputs. Employing multi-dimension measures, we find that corporate PEPU has a noteworthy negative impact on the quality of corporate innovation output. Further analysis shows that firms scale down their R&D investment intensity and gravitate towards conservative R&D projects as firms’ PEPU rises. Additionally, the firm will enhance its collaborative R&D efforts with other firms to mitigate risk. These strategic R&D behaviors guarantee the quantitative stability of a firm’s innovation output, but they also undermine firms’ innovation quality. These findings have significant policy implications for the policy-making process in emerging markets.

Sex/gender differences in general cognitive abilities: an investigation using the Leiter-3.

Research has shown that differences between males and females are not in general intelligence, but only in some specific factors and tasks. We used the Italian standardization of the Leiter-3, which is a completely nonverbal cognitive battery, to investigate the nature of sex/gender (we used sex/gender to reflect the awareness that the effects of biological 'sex' and socially constructed 'gender' cannot be easily separated and that most individuals' identities are informed by both sex and gender) differences. In doing so we used a multigroup confirmatory factor analysis approach. Results confirmed that males and females perform similarly in general intelligence, but present with some specificities. Males perform better on some, but not all, tasks requiring the spatial manipulation of the stimuli, but females consistently outperform males in tasks such as the nonverbal Stroop, requiring inhibition and attention control to a larger extent. The clinical and practical implications of our findings are considerable. The identification of specific cognitive strengths and weaknesses in males and females underscores the importance of tailored approaches in clinical assessments and interventions.

Tradisi Akademik Sekolah Dasar Unggulan di Sekolah Dasar Alam

Studying academic traditions in leading primary schools in Malang, especially in SD Alam Ar-Rohmah, is crucial for deeper examination. This is because such studies are incessantly debated. This writing aims to understand three aspects: First, the paradigm of academic tradition in SD Alam Ar-Rohmah. Second, internal and external factors influence the academic tradition in the school. Third, the positive and negative implications of the academic tradition on students in the school. The methods employed include observation, interviews, and documentation along with a literature review using a content analysis approach. The findings reveal three aspects: First, the paradigm of academic tradition in SD Alam Ar-Rohmah encompasses three forms: (1) distinctive curriculum, (2) Islamic morning stories, and (3) market day. Second, internal factors influencing the academic tradition in the school consist of three elements: (1) school principal's strategies, (2) teachers' creativity, and (3) teaching methods. As for external factors, three influences are identified: (1) school environment, (2) families, and (3) community. Third, the positive implications of the academic tradition on students include (1) high achievements, (2) excellent accreditation, and (3) increased student quantity. In conclusion, this study demonstrates that SD Alam Ar-Rohmah has established itself as a leading primary school with a strong academic tradition.

Pathway-based analyses of gene expression profiles at low doses of ionizing radiation

Pathway-based analyses of gene expression profiles at low doses of ionizing radiation

High Frequency Response of Volatile Memristors

AbstractIn this theoretical study, the high‐frequency response of the electrothermal NbO2‐Mott threshold switch is focused, a real‐world electronic device, which has been proved to be relevant in several applications and is classified as a volatile memristor. Memristors of this kind, have been shown to exhibit distinctive non‐linear behaviors crucial for cutting‐edge neuromorphic circuits. In accordance with well‐established models for these devices, their resistances depend on their body temperatures, which evolve over time following Newton's Law of Cooling. Here, it is demonstrated that HP's NbO2‐Mott memristor can manifest up to three distinct steady‐state oscillatory behaviors under a suitable high‐frequency periodic voltage input, showcasing increased versatility despite its volatile nature. Additionally, when subjected to a high‐frequency periodic voltage signal, the device body temperature oscillates with a negligible peak‐to‐peak amplitude. Since the temperature remains almost constant over an input cycle, the devices under study behave as linear resistors during each input cycle. Based on these insights, this paper presents analytical equations characterizing the response of the NbO2‐Mott memristor to high‐frequency voltage inputs, demarcating regions in the state space where distinct initial conditions lead to various asymptotic oscillatory behaviors. Importantly, the mathematical methods introduced in this manuscript are applicable to any volatile electrothermal resistive switch. Additionally, this work presents analytical equations that accurately reproduce the temperature time‐waveform of the studied device during both its transient and steady‐state phases when subjected to a zero‐mean sinusoidal voltage input oscillating in the high‐frequency limit. This analytical approach not only increases the comprehension of volatile electrothermal memristors but also provides a theoretical framework to harness the enhanced dynamical capabilities of real‐world volatile memristors in practical applications.