Measures Of Cohesion Research Articles

A grounded theory of cognitive analytic reflective practice groups

AbstractObjectivesWhilst cognitive analytic therapy (CAT) is increasingly used as an indirect intervention, there is little evidence of how the approach can be applied to reflective practice. This study sought to develop a process model of cognitive analytic reflective practice (CARP) groups.DesignConstructivist grounded theory approach supplemented by quantitative measures of helpfulness and group cohesion.MethodsTwenty‐four participants, working within four staff teams in a secure children's home, attended four CARP groups over a 1‐year period. Sessions were audio recorded, transcribed and checked for model fidelity and then analysed using grounded theory. Theoretical sampling was achieved via conducting focus groups with teams informed by the emergent categories, and using sessional measures of group cohesion and helpfulness to confirm theoretical saturation.ResultsThe model constructed had three interrelated main categories: ‘facilitator processes: establishing a reflective space’, ‘group processes: widening awareness of the self, others, and system’ and ‘outcomes: changing relational dynamics and finding exits.’ The model was validated by evidence from the measures.ConclusionsThe model offers an empirical understanding of how CAT informs reflective practice through a better understanding of reciprocity in the dynamics of care systems.

Social Cohesion in Different Periods of the Pandemic: What Works in Reducing COVID-19 Mortality

Abstract Background Inconsistent results were reported regarding the effects of social cohesion dimensions on COVID-19 mortality rate (MR). Most studies have indicated that trust in civil services, but not participating in social activities, reduces COVID-19 MR, possibly because of the highly contagious nature of this disease. In this study, we investigated how the effects of various dimensions of social cohesion on COVID-19 MR vary across different phases of the pandemic. Methods This longitudinal study was conducted using data from 86 countries that participated in the 2017-2020 World Values Survey. The measures of social cohesion were identified by aggregating survey responses to the country level. COVID-19 MR was calculated-using data from the European Centre for Disease Prevention and Control-separately for three distinct periods during the pandemic (January 2021-June 2022). A factor analysis was conducted to identify the dimensions of social cohesion, and negative binomial regression models were constructed to analyze data for each period. Results The factor analysis revealed three dimensions of social cohesion: social participation and inclusion, health service equality, and trust in civil services and democracy. Our findings suggest that each dimension of social cohesion uniquely affected COVID-19 outcomes in different periods of the pandemic. Trust in civil services and a positive attitude toward democracy are strongly associated with a low COVID-19 MR. However, this association was observed only in the early and middle stages of the pandemic. By contrast, our study demonstrated that in the late stage of the pandemic, increased social participation and inclusion helped combat COVID-19. Conclusions This study underscores the importance of collective cohesion and solidarity in mobilizing public responses against pandemic situations. This study emphasizes that preventive or regulatory interventions should be tailored to different phases of a pandemic. Key messages • COVID-19 mortality rate was negatively associated with trust in civil services during the early two periods and with social participation and social inclusion during the late period of the pandemic. • This study emphasizes that preventive or regulatory interventions should be tailored to different phases of a pandemic.

The eroding power of anti-immigrant attitudes for social cohesion in Singapore: more myth than fact?

This paper analyses the impact of anti-immigrant attitudes on social cohesion in Singapore. The OLS regression models show that anti-immigrant attitudes have a negative influence on social cohesion in all analyses, but this influence is weak and falls behind the ambiguous influence of patriotism. In some of the data, there is a significant difference in social cohesion between the centre and the peripheral districts of Singapore, which can only be attributed to a small extent to composition effects. The results of the analyses thus show that the partially state-led measures for social cohesion in a post-colonial society are indeed effective. However, the multicultural Singaporean society obviously also reacts to cohesion policy measures in a group-specific manner. It is noticeable that social cohesion and an open culture for newcomers cannot be thought of separately. These policies should therefore focus even more strongly than before on social cohesion as societal cohesion.

Standing out while fitting in: An objective measure of visual branding cohesion across a product portfolio

This research develops a new metric (PBCM) that can identify products within a portfolio that are eroding visual branding cohesion. We show how this new measure gives results equivalent to consumer evaluations of cohesion, without costly and time intensive data collection. The sampling frame for this research is 10 portfolios from five categories (dry dog food, instant coffee, toothpaste, shower gel and chewing gum) in the United Kingdom. In addition, 626 consumers were surveyed to investigate how PBCM affects a consumer’s ability to match an individual product back to its portfolio and recall the brand name. We find that products from high cohesion portfolios have significantly higher (17%) correct brand recall than those from low cohesion portfolios and are matched back to their portfolio by more than twice as many respondents (79% v 35%), significantly faster (2.3 vs. 3.8 minutes).

Use of noninvasive measurement of the indocyanine green plasma disappearance rate in patients with septic shock.

Our aim was to analyse the relation between serial values of the indocyanine green plasma disappearance rate (ICG-PDR) with hospital mortality in the first 48 hours of ICU admission in patients with septic shock. A prospective observational study was carried out over 12 months of patients admitted to the ICU with septic shock. Each patient underwent noninvasive determination of ICG-PDR at 24 and 48 hours with the LiMON® module. Follow-up was performed until hospital discharge or exitus. 63 patients. Age 61.1±12.3 years. 60.3% men. SOFA score on admission 8.7±3.3, APACHE II score was 27.9±10.7 points. A total of 44.4% of patients died. The ICG-PDR values in the first 24 hours of ICU admission were lower in nonsurvivors: 10.5 (5.7-13.0)%/min vs. 15.9 (11.4-28.0)%/min, p <0.001. Furthermore, in nonsurvivors, there was no improvement in ICG-PDR between 24 h and 48 h, while in survivors, there was an increase of 25%: 15.9 (11.4-28.0)%/min and 20.9 (18.0-27.0)%/min, p=0.020. The silhouette measure of ICG-PDR cohesion and separation for the clusters analysed (nonsurvivors and survivors) was satisfactory (0.6). ICG-PDR<11.7%/min was related to in-hospital mortality, ICG-PDR> 18%/min to survival, and the interval between 11.7% and 18%/min covered a range of uncertainty. In the two-stage cluster, ICG-PDR, SOFA and APACHE II present satisfactory predictive scores 24 hours after patient admission. ICG-PDR in our setting is a useful clinical prognostic tool and could optimise the decision tree in patients with septic shock.

Effects of initial soil moisture on rill erodibility and critical shear stress factors in the WEPP model across diverse soil types

Rill erosion, a significant issue in agricultural regions, is intricately linked to initial soil moisture conditions, affecting the development of concentrated flow erosion processes. However, understanding its dynamics amidst varying soil moisture conditions remain challenging. This study aimed to assess the impact of different soil moisture levels on rill erodibility parameters in the Water Erosion Prediction Project (WEPP) model and to evaluate soil cohesion across a spectrum of soils. Through laboratory experiments employing a small V-shaped rill channel, we investigated rill erodibility (Kr) and critical hydraulic shear stress (τcr), under three soil moisture scenarios: initially dry, saturated, and drainage, with incremental surface inflow rates. Additionally, we examined the efficiency of soil cohesion obtained from an Automated Soil Cohesion Measurement Apparatus in predicting Kr and τcr across various soil textures. Our analysis encompassed twenty soils representing nine texture classes, revealing significant correlations between basic soil properties, cohesion parameters, and WEPP model rill erodibility. Notably, initial soil moisture conditions exerted substantial influence on erodibility potentials. Soils with higher silt contents demonstrated better fits in terms of Nash-Sutcliffe model efficiency, particularly under initially dry and saturated conditions. However, predictions for initially drained soils yielded poor fits, emphasizing the intricate interplay between soil properties and hydrological conditions. In conclusion, our findings emphasize the critical role of topsoil water dynamics in rill erodibility. We propose that soil cohesion serves as a valuable predictor, complementing friction forces within the soil and enhancing simulations of rill erodibility under shallow flow conditions in rills, particularly in next-generation process-based modeling approaches.

Validation of the German version of the Perceived Cohesion Scale.

Team or group cohesion is a multifaceted construct with a variety of definitions and measurement instruments. However, most of these measures are context and group-specific and/or time-consuming. There is no adaptable and economic measure of group cohesion in Germany. Therefore, the aim of this study was to validate the German version of the 6-item Perceived Cohesion Scale (PCS) in a sample of adult nurses in a German University Hospital. The German version of the PCS was generated according to existing guidelines. Confirmatory factor analysis was conducted to assess factor structure. Reliability was tested via internal consistency. To assess convergent and divergent validity, the authors applied the Copenhagen Psychosocial Questionnaire (COPSOQ), the Enhancing Recovery in Coronary Heart Disease Patients (ENRICHD) Social Support Inventory (ESSI), the Effort-Reward Imbalance (ERI) scale and the Patient Health Questionnaire (PHQ-4). The confirmatory factor analysis confirmed a 2-factor structure. Psychometric properties of the German PCS prove satisfactory. Internal consistency was excellent for the whole scale (α = 0.95), as well as for both subscales: sense of belonging (SOB) (α = 0.94) and morale (MOR) (α = 0.93). Moderate to strong correlations with the subscales of COPSOQ (Kendall's Tau (τ) = 0.239 - 0.471) indicated very good convergent validity. Regarding divergent validity, the correlations of the PCS subscales and the PHQ-4 were low (τ = -0.109-[-0.143]), as were the correlations with ESSI (τ = 0.045-0.136). Correlations with ERI were low to moderate (τ = -0.181-0.283). The German version of the PCS showed good psychometric properties. Due to its economic and universal deployment, group cohesion can be measured in a variety of contexts and settings. Int J Occup Med Environ Health. 2024;37(4).

Abstract A052: The association of perceived neighborhood environment with physical and mental health status among cancer survivors in the All of Us Research Program

Abstract Background Neighborhood environment has been recognized as a key determinant of health. Neighborhood disorder refers to physical and social characteristics of neighborhoods that may signal the breakdown of order and social control. Previous studies have reported that neighborhood disorder, such as high levels of noise, vandalism, abandoned buildings, crime, and drug and alcohol use, is associated with poor self-reported health. In contrast, neighborhood social cohesion and the extent of connectedness in society have positive effects on physical and mental health. Little studies, however, have comprehensively examined the association between perceived neighborhood environment and health outcomes among cancer survivors. We examined and found this significant association among cancer survivors. Method We used survey and electronic health records data on cancer survivors aged ≥18 years (N=10,051) from All of Us Controlled Tier Dataset v7 (summer 2017-July 2022), including survey data on 21 items about neighborhood environment, neighborhood order, disorder, and social cohesion. Eleven items were used to measure perceived neighborhood disorder, six items were used to measure perceived neighborhood order, and four items were used to measure perceived social cohesion. Logistic regression models were used to estimate the association between each measure of neighborhood order, disorder, or social cohesion and physical and mental health status (poor/fair versus very good/excellent), adjusted for 1) age and sex; 2) age, sex, race/ethnicity, educational attainment, annual household income, employment, health insurance, marital status, living alone, house ownership, nativity, smoking, and heavy alcohol drinking. Results Cancer survivors living in neighborhoods with high level of order and social cohesion were less likely to report poor or fair physical health. For example, cancer survivors who perceived their neighborhood as sharing the same values were less likely to report poor or fair physical health (OR=0.49; 95% CI=0.39- 0.61). Additionally, cancer survivors who felt their neighborhood was safe were less likely to report poor or fair physical health (OR=0.71; 95% CI=0.55-0.92). In contrast, cancer survivors residing in neighborhood with disorder characteristics were more likely to report poor or fair physical health. Specifically, those living in neighborhood with common vandalism were more likely to report poor or fair physical health (OR=1.40; 95% CI=1.08-1.80). Furthermore, cancer survivors who perceived high level of drug use in their neighborhood were more likely to report poor or fair physical health (OR=1.49; 95% CI=1.19-1.88). Similar associations were observed between 19 neighborhood characteristics and mental health status. Conclusions Most neighborhood characteristics evaluated in this study were associated with self-reported physical and mental health status among cancer survivors. These findings suggest that improving built environment and social support could enhance perceived health and quality of life in this population. Citation Format: Dongjun Lee, Farhad Islami, Ahmedin Jemal, Hyunjung Lee. The association of perceived neighborhood environment with physical and mental health status among cancer survivors in the All of Us Research Program [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr A052.

Frustrated marriage? The ideological distance of members of congress from their parties in Latin America

Are legislators ideologically close to their co-partisans? And, when not, what policies drive the lack of party unity? To address these questions, we propose two measures of intra-party ideological cohesion: dissonance and frustration. Based on a survey of legislators across 18 Latin American countries, we show that half of the region’s representatives self-identify as substantially far from the mean of their parties (dissonance) and almost 40% perceive large differences (frustration). Relying on a series of statistical tests, we find that these patterns are distinct for left-wing and right-wing legislators. The right is more dissonant than frustrated, and they are also more dissonant than the left. In terms of policy, we show that moral issues drive dissonance and frustration on both sides of the ideological spectrum, but disagreements on economic topics are more correlated with ideological distance for the left than the right. In presenting new measurements of intra-party disagreements, our paper proposes new pathways for the study of party cohesion.

An enhanced conventional neural network schema for structural class-based software fault prediction

ABSTRACT Malicious software detection is the most prominent process required by various industries to avoid server failure. It is required to detect malicious software accurately to avoid time and cost wastage. Various research works have been introduced earlier for the detection of malicious software. In the existing work Support Vector Machine (SVM) is introduced for malicious software detection. However, existing works cannot perform well where there are error modules in the software. It is addressed in this suggested study by developing Coupling and Cohesion Metrics-based Fault Detection (CCMFD). In this research work, structural measures are mainly examined which come under the cohesion measures and comprise deficient cohesion in approaches (LCOM), and Conceptual Coupling between Object Classes (CCBO). Failure situations and measures relating to information flow are used in other techniques. A high-quality service has a low coupling and a high cohesiveness. These extracted features will be given as input to the enhanced Conventional Neural Network (CNN) for software mistake forecasting. A complete study analysis is done in a Java simulator, indicating that the suggested approach tends to have superior fault prediction outcomes than the current method.

Exposure to climate events and mental health: Risk and protective factors from the California Health Interview Survey

There is increasing awareness of the effects of climate change on mental health, but more work on understanding risk and protective factors is needed. The 2021 California Health Interview Survey included new questions about exposure to extreme weather events and mental health responses. This study aims to identify how individual factors and neighborhood social cohesion are associated with negative mental health effects of exposure to extreme weather events. In this cross-sectional, representative study, we used data from the 2021 California Health Interview Survey to analyze the association between respondent characteristics and self-report of negative mental health effects following exposure to extreme weather events. Univariate and multivariate logistic regression models were used, adjusting for individual-level sociodemographics and measures of neighborhood social cohesion. We found that 53% of the sample reported being affected by climate events (n = 12,955), and of these, 22.8% (n = 2,955) reported a negative impact on their mental health. Respondents who were younger, White, female, college-educated, or living in a rural area were more likely to report adverse mental health effects of climate events for themselves or household members. Individuals who had experienced property damage were much more likely to report negative mental health effects due to climate events [property damage adjusted OR 3.73, 95% CI 2.82–3.76]. This study identifies subgroups that may have higher vulnerability to the mental health effects of climate change events. Future research is needed to develop targeted prevention and outreach interventions to these subgroups to build individual- and community-level resilience.

Hyperauthored papers disproportionately amplify important egocentric network metrics

Abstract Hyperauthorship, a phenomenon whereby there are a disproportionately large number of authors on a single paper, is increasingly common in several scientific disciplines, but with unknown consequences for network metrics used to study scientific collaboration. The validity of coauthorship as a proxy for scientific collaboration is affected by this. Using bibliometric data from publications in the field of genomics, we examine the impact of hyperauthorship on metrics of scientific collaboration, and propose a method to determine a suitable cutoff threshold for hyperauthored papers and compare coauthorship networks with and without hyperauthored works. Our analysis reveals that including hyperauthored papers dramatically impacts the structural positioning of central authors and the topological characteristics of the network, while producing small influences on whole-network cohesion measures. We present two solutions to minimize the impact of hyperauthorship: using a mathematically grounded and reproducible calculation of threshold cutoff to exclude hyperauthored papers or fractional counting to weight network results. Our findings affirm the structural influences of hyperauthored papers and suggest that scholars should be mindful when using coauthorship networks to study scientific collaboration.

Family meals are associated with lower substance use in female adolescents.

Adolescents, especially female youth, who have more family meals tend to be at lower risk for substance use. The present study tested whether family meals relate to substance use count and frequency during high school, whether associations differ by gender, and whether other family-related variables explain these associations. A community sample of 316 adolescents (Mage = 16.40, SD = 0.74; 56.96% female; 41.77% Latine, 23.10% Asian American, 29.11% European American, 6.01% from other ethnic backgrounds including Middle Eastern and African American) reported the number of substances they have ever used and how often they used alcohol, marijuana, and cigarettes, and completed measures of parental support and family cohesion. Across 15 days, they reported whether they had a family meal, got along with parents, and spent leisure time with their family each day. Regression models tested associations between frequency of family meals and substance use, whether associations differed by gender, and whether associations were explained by other family-related variables. Results indicated that more frequent family meals were associated with lower substance use count and less frequent alcohol, marijuana, and cigarette use among female adolescents but not male adolescents. Other daily family experiences were unrelated to substance use, and family meal frequency was independently related to lower substance use after accounting for parental support and family cohesion. Taken together, more frequent family meals in high school may reduce substance use risk for female adolescents, and interventions could consider promoting family meals in addition to other positive family values.

Combined measures in lake restoration – A powerful approach as exemplified from Lake Groote Melanen (the Netherlands)

Controlling lake eutrophication is a challenge. A case-specific diagnostics driven approach is recommended that will guide to a suite of measures most promising in restoration of eutrophic lakes as exemplified by the case of the shallow lake Groote Melanen, The Netherlands. A lake system analysis identified external and internal nutrient load as main reasons for poor water quality and reoccurring cyanobacterial blooms in the lake. Based on this analysis, a package of restoration measures was implemented between January 2015 and May 2016. These measures included fish removal, dredging, capping of peat rich sediment with sand and an active barrier (lanthanum-modified bentonite), diversion of two inlet streams, reconstruction of banks, and planting macrophytes. Dredging and sand capping caused temporarily elevated turbidity and suspended solids concentrations, while addition of the lanthanum-modified clay caused a temporary exceedance of the Dutch La standard for freshwaters. Diversion of inflow streams caused 35 % less water inflow and larger water level fluctuations, but the lake remained water transporting with strongly improved water quality as was revealed by comparing five years pre-intervention water quality data with five years’ post-intervention data. Total phosphorus concentration in the water column was reduced by 93 % from 0.47 mg P l-1 before the intervention to 0.03 mg P l-1 after the intervention, total nitrogen by 66 % from 1.27 to 0.21 mg N l-1, total chlorophyll-a by 75 % from 68 to 16 µg l-1, cyanobacteria chlorophyll-a by 88 % from 32 to 4 µg l-1. Turbidity had declined by 58 % from 23.5 FTU to on average 9.9 FTU. No cyanobacteria blooms were recorded over the entire post-intervention monitoring period (2016–2021). Submerged macrophytes increased from complete absence before intervention to around 10 %–15 % coverage after intervention. Repeated fish removal lowered the fish stock to below 100 kg ha-1 with 12 % of bream and carp remaining. Hence, the package of cohesive measures that was based on a thorough diagnosis resulted in rapidly, strongly and enduringly improved water quality. This case provides evidence for the power of combining measures in restoring eutrophic lakes.

Online peer support groups for individuals who hear voices: protocol for a nonrandomised feasibility study

ABSTRACT Background Hearing Voices Groups (HVGs) have proliferated internationally. They are premised on the notion that connections between peers facilitate personal recovery. Little systematic research exists into if, and how, HVGs may be effective, especially when convened online. This paper aims to harmonise standardised research methodology with the liberatory, survivor-led ethos of many HVGs to outline a protocol for the first longitudinal, nonrandomised trial of an online HVG to take place within UK mental health services. Methods Six to ten adults who hear voices will be recruited from both community and UK National Health Service (NHS) settings to participate in a six-month peer-support group that is delivered via videoconference. Participants will complete questionnaires assessing social support, voice-hearing and feelings of personal recovery and qualitative interviews at baseline and at the end of the group. Participants will also complete measures of group cohesion at weeks 4 and 12. Results Data will be analysed for feasibility, acceptability and safety. Discussion This is the first longitudinal study evaluating the feasibility and acceptability of an online HVG held within the NHS. The findings may provide insights into the impact of such interventions and inform the design of a future, definitive study.

Sailfish generate foraging opportunities for seabirds in multi-species predator aggregations.

While various marine predators form associations, the most commonly studied are those between subsurface predators and seabirds, with gulls, shearwaters or terns frequently co-occurring with dolphins, billfish or tuna. However, the mechanisms underlying these associations remain poorly understood. Three hypotheses have been proposed to explain the prevalence of these associations: (1) subsurface predators herd prey to the surface and make prey accessible to birds, (2) subsurface predators damage prey close to the surface and thereby provide food scraps to birds, and (3) attacks of underwater predators lower the cohesion of prey groups and thereby their collective defences making the prey easier to be captured by birds. Using drone footage, we investigated the interaction between Indo-Pacific sailfish (Istiophorus platypterus) and terns (Onychoprion sp.) preying on schooling fish off the eastern coast of the Malaysian peninsula. Through spatio-temporal analysis of the hunting behaviour of the two predatory species and direct measures of prey cohesion we showed that terns attacked when school cohesion was low, and that this decrease in cohesion was frequently caused by sailfish attacks. Therefore, we propose that sailfish created a by-product benefit for the bird species, lending support to the hypothesis that lowering cohesion can facilitate associations between subsurface predators and seabirds.

Assessing the psychometric properties of the Army STARRS’ vertical unit cohesion scale: A large-scale, longitudinal study

ABSTRACT Unit cohesion is the extent to which military service members feel committed to and supported by their military unit or, conversely, feel overlooked, neglected, and/or alienated. Unit cohesion reflects an important aspect of military social support and can act as a protective factor against mental health challenges, particularly in challenging situations. Theoretical suppositions and emerging evidence suggest that different types of unit support, specifically, vertical unit cohesion and horizontal unit cohesion, uniquely matter for service member well-being. Vertical unit cohesion (support from leaders in the unit and other higher-ranking positions) may be of universal importance to service members with implications for career progression and personal wellbeing, while horizontal unit cohesion (support from fellow unit members and peers) may be of importance under certain circumstances. Informed by the psychometric theory of scale development and validation, the dimensionality of unit cohesion theory, and the need for brief, sound measurement tools, this study first examined the psychometric properties of the Army STARRS four-item Vertical Unit Cohesion Scale in a longitudinal analysis with a large, diverse sample of Soldiers from the Pre/Post Deployment Study component of the Army STARRS dataset (N = 10,116). Then, exploratory analyses were conducted to examine the properties of the Horizontal Unit Cohesion Scale and understand the relationship between vertical and horizontal unit cohesion. Strong evidence for the Vertical Unit Cohesion Scale’s psychometric soundness was established regarding factor structure, measurement invariance overtime, and construct validity. Conversely, preliminary evidence suggests that the three-item measure of Horizontal Unit Cohesion should be used with caution. Implications for researchers and military leadership are provided.

Cohesion measurements between variables and methods using component-based software systems

The practice of leveraging previously created software components to progress new software is identified as component-based software engineering (CBSE). Good software engineering design is the foundation of CBSE principles. The black box approach that underpins CBSE hides the execution of components in nature, and the components communicate with one another using strictly delineated interfaces. Component platforms are shared, which lowers the price of creation. To ascertain a system's complexity, various software metrics are employed. For superiority in software intricacy, coupling would be minimal, and cohesiveness must be high. It is predetermined that coupling should be low and cohesion should be increased for refinement in software complexity. We are identifying the combination of different software systems and improving the methods for doing so with our approach. Proposed: Cohm (cohesion of methods) and Cohv (cohesion of variables) are two cohesion metrics that have been proposed. The cohesiveness metrics in this study have been analytically and empirically evaluated, and a comparison has been made between them. Additionally, an effort was made to give the outcomes of an empirical estimation based on the case study. The T-test is used to determine the consequences of the metrics, and Python is used to validate the metrics. Python or R programming and the Matlab tool are used to determine the relationship between various variables and metrics. Findings: The consequence of the current investigation is very encouraging and might be used to estimate the involvedness of the parts. The proportional analysis of the proposed metrics and various cohesion metrics reveals that the suggested metrics are more cohesive than the present metrics, increasing the likelihood that they can be reused when creating new applications.

Profiles of health literacy and digital health literacy in clusters of hospitalised patients: a single-centre, cross-sectional study

ObjectiveTo investigate health literacy (HL) and digital health literacy (eHL) among patients hospitalised in surgical and medical wards using a cluster analysis approach.DesignCross‐sectional study using Ward’s hierarchical clustering method to...

Detecting Overlapping Communities Based on Influence-Spreading Matrix and Local Maxima of a Quality Function

Community detection is a widely studied topic in network structure analysis. We propose a community detection method based on the search for the local maxima of an objective function. This objective function reflects the quality of candidate communities in the network structure. The objective function can be constructed from a probability matrix that describes interactions in a network. Different models, such as network structure models and network flow models, can be used to build the probability matrix, and it acts as a link between network models and community detection models. In our influence-spreading model, the probability matrix is called an influence-spreading matrix, which describes the directed influence between all pairs of nodes in the network. By using the local maxima of an objective function, our method can standardise and help in comparing different definitions and approaches of community detection. Our proposed approach can detect overlapping and hierarchical communities and their building blocks within a network. To compare different structures in the network, we define a cohesion measure. The objective function can be expressed as a sum of these cohesion measures. We also discuss the probability of community formation to analyse a different aspect of group behaviour in a network. It is essential to recognise that this concept is separate from the notion of community cohesion, which emphasises the need for varying objective functions in different applications. Furthermore, we demonstrate that normalising objective functions by the size of detected communities can alter their rankings.