POWER LAW DISTRIBUTION AS A COMPONENT OF THE VERTEX DEGREE DISTRIBUTION ON A SOCIAL UNIVERSITY NETWORK COURSE

The aim of this paper is to analyze a collection of data gathered from surveys held every three weeks in a Spring Course of the Economic Faculty in the University “Ismail Qemali”of Vlora, Albania. The data set for each student also contains the names of other students through which he/she have a “social relationship”. This social relationship includes frequent communications, discussions on exercise solutions, and sitting usually close to each other in the class. We have constructed four social simple graphs and have analyzed them focusing only on degrees. In addition, we fit discrete power law degree distribution on the tail and their evolution through time. In analyzing the data, we employed the R platform

Assessing Clustering in a Social University Network Course

A collection of data is gathered from surveys held in a Spring Course of the Economic Faculty in the University “Ismail Qemali” of Vlora, Albania. The data set for each student contains the names of the other students through which he/she have a “social relationship”. This relationship includes frequent communications, discussions on exercise solutions, and sitting usually close to each other in the class. We have constructed. At the end of the course, a final network based on this type of relationship. We are particularly interested on the clustering coefficient of this network and assessing it’s “significance”, in the sense of being somehow unusual or unexpected. Simulated random graph models, using R platform, are used to test the “significance” of the observed clustering coefficient

POWER LAW DISTRIBUTION AS A COMPONENT OF THE VERTEX DEGREE DISTRIBUTION ON A SOCIAL UNIVERSITY NETWORK COURSE

The aim of this paper is to analyze a collection of data gathered from surveys held every three weeks in a Spring Course of the Economic Faculty in the University “Ismail Qemali”of Vlora, Albania. The data set for each student also contains the names of other students through which he/she have a “social relationship”. This social relationship includes frequent communications, discussions on exercise solutions, and sitting usually close to each other in the class. We have constructed four social simple graphs and have analyzed them focusing only on degrees. In addition, we fit discrete power law degree distribution on the tail and their evolution through time. In analyzing the data, we employed the R platform

Descriptive Analysis of Characteristics: A Case Study of a Phone Call Network Graph

Nowadays, systematic collection of data has necessitated a detailed statistical analysis as a necessary tool to make a mathematical characterization of them with the purpose of gathering information about the present or the future. Our aim in this paper is to analyze a landline phone call network graph from the perspective of descriptive analysis. We explore the characteristics and structural properties of the network graph constructed using an anonymous collection of data gathered from a Call Data Records of a telecommunication operator center located in south of Albania. The R statistical computing platform is used for network graph analysis

Statistical Issues in Predictive Modelling using Bootstrap Method

A model is a statement of reality or its approximation. Most phenomena in the social sciences are extremely complex. With a model we simplify the reality and focus on a manageable number of factors. It is impossible to completely understand why consumers default and identify all the factors influencing customer’s default behavior. The bank manager sets up a statistical model that relates customer’s default behavior to only two important factors, the income and the education. There surely are thousands of other variables that may influence customer’s default behavior. This article describes the fundamentals of a statistical model building. We begin our discussion on the managerial justification for building a statistical model. Then we discuss three important statistical issues that are of prime importance to database marketers: model/variable selection, treatment of missing data, and evaluation of the model using Bootstrap Method

Poststroke psychosis: a systematic review

A preregistered systematic review of poststroke psychosis examining clinical characteristics, prevalence, diagnostic procedures, lesion location, treatments, risk factors and outcome. Neuropsychiatric outcomes following stroke are common and severely impact quality of life. No previous reviews have focused on poststroke psychosis despite clear clinical need. CINAHL, MEDLINE and PsychINFO were searched for studies on poststroke psychosis published between 1975 and 2016. Reviewers independently selected studies for inclusion, extracted data and rated study quality. Out of 2442 references, 76 met inclusion criteria. Average age for poststroke psychosis was 66.6 years with slightly more males than females affected. Delayed onset was common. Neurological presentation was typical for stroke, but a significant minority had otherwise ‘silent strokes’. The most common psychosis was delusional disorder, followed by schizophrenia-like psychosis and mood disorder with psychotic features. Estimated delusion prevalence was 4.67% (95% CI 2.30% to 7.79%) and hallucinations 5.05% (95% CI 1.84% to 9.65%). Twelve-year incidence was 6.7%. No systematic treatment studies were found. Case studies frequently report symptom remission after antipsychotics, but serious concerns about under-representation of poor outcome remain. Lesions were typically right hemisphere, particularly frontal, temporal and parietal regions, and the right caudate nucleus. In general, poststroke psychosis was associated with poor functional outcomes and high mortality. Poor methodological quality of studies was a significant limitation. Psychosis considerably adds to illness burden of stroke. Delayed onset suggests a window for early intervention. Studies on the safety and efficacy of antipsychotics in this population are urgently needed

Investigation of possible risk factors for depression in Alzheimer's disease: A systematic review of the evidence

Background: Depression is common in people with Alzheimer's disease (AD), and is associated with increased risk of institutionalization and mortality. Understanding risk factors for depression in AD is key to its development and treatment. / Methods: We searched the MEDLINE, EMBASE, PsycINFO, and CINAL databases for longitudinal prospective cohort studies that evaluated risk factors for depression in people with AD. Two authors independently selected articles for inclusion and assessed quality of studies using predetermined criteria. / Results: In seven studies that met the inclusion criteria, 2029 participants were followed up for a median of 5 years. Gender and educational attainment were not predictors of depression risk. History of a past psychiatric disorder and greater cognitive impairment predicted increased risk of depression in more than one study. In single studies, younger age, having a family history of psychiatric disorder, neuroticism, functional decline, presence of sleep disturbance and aggression, and increased cardiovascular risk predicted depression risk. Not being within 6 months of dementia onset and, counterintuitively having two comorbid disorders were protective factors in one study. / Limitations: A small number of studies exist overall and only a few have examined the same risk factors. Most of the studies have measured depression using scales that are not validated in AD. / Conclusions: These results inform a preliminary model of depression risk in people with AD. Unlike in the general population, men and women and those with higher and lower educational levels of attainment may be equally at risk of depression. Clinicians should be aware of these possible differences in the risk profile for depression in AD populations, to assist detection and enable early treatment. Interventions to delay cognitive and functional decline may reduce depression risk

Psychological treatments for depression and anxiety in dementia and mild cognitive impairment

BACKGROUND: Experiencing anxiety and depression is very common in people with dementia and mild cognitive impairment (MCI). Psychological interventions have been suggested as a potential treatment for these populations. Current research suggests that people with dementia and MCI have limited opportunities for psychological treatments aimed at improving their well-being. A systematic review of the evidence on their effectiveness is likely to be useful in terms of improving outcomes for patients and for future recommendations for practice. OBJECTIVES: The main objective of this review was to assess the effectiveness of psychological interventions in reducing anxiety and depression in people with dementia or mild cognitive impairment (MCI). SEARCH METHODS: We searched the Cochrane Dementia and Cognitive Improvement Group Specialized Register and additional sources for both published and unpublished data. Selection criteria We included randomised controlled trials (RCTs) comparing a psychological intervention with usual care or a placebo intervention (social contact control) in people with dementia or MCI. DATA COLLECTION AND ANALYSIS: Two review authors worked independently to select trials, extract data and assess studies for risk of bias, using a data extraction form. We contacted authors when further information was not available from the published articles. MAIN RESULTS: Six RCTs involving 439 participants with dementia were included in the review, but no studies of participants with MCI were identified. The studies included people with dementia living in the community or in nursing home care and were carried out in several countries. Only one of the studies was classified as low risk of bias. Five studies were at unclear or high risk of bias due to uncertainties around randomisation, blinding and selective reporting of results. The studies used the different psychological approaches of cognitive behavioural therapy (CBT), interpersonal therapy and counselling. Two studies were of multimodal interventions including a specific psychological therapy. The comparison groups received either usual care, attention-control educational programs, diagnostic feedback or services slightly above usual care. Meta-analysis showed a positive effect of psychological treatments on depression (6 trials, 439 participants, standardised mean difference (SMD) -0.22; 95% confidence interval (CI) -0.41 to -0.03, moderate quality evidence) and on clinician-rated anxiety (2 trials, 65 participants, mean difference (MD) -4.57; 95% CI -7.81 to -1.32, low quality evidence), but not on self-rated anxiety (2 trials, SMD 0.05; 95% CI -0.44 to 0.54) or carer-rated anxiety (1 trial, MD -2.40; 95% CI -4.96 to 0.16). Results were compatible with both benefit and harm on the secondary outcomes of patient quality of life, activities of daily living (ADLs), neuropsychiatric symptoms and cognition, or on carers' self-rated depressive symptoms, but most of the studies did not measure these outcomes. There were no reports of adverse events. AUTHORS' CONCLUSIONS: We found evidence that psychological interventions added to usual care can reduce symptoms of depression and clinician-rated anxiety for people with dementia. We conclude that psychological interventions have the potential to improve patient well-being. Further high quality studies are needed to investigate which treatments are most effective and to evaluate the effect of psychological interventions in people with MCI

Risk factors for apathy in Alzheimer’s disease: A systematic review of longitudinal evidence

BACKGROUND: Apathy is frequent and persistent in Alzheimer’s disease (AD), associated with poor prognosis and carer distress; yet our knowledge of risk factors remains limited. AIMS: To identify risk factors associated with apathy incidence and progression in AD over time. METHODS: We systematically reviewed evidence based on longitudinal studies assessing risk factors for apathy in AD up to June 2021. Two authors independently assessed article eligibility and rated quality. RESULTS: 13,280 articles were screened, of which 13 met inclusion criteria. Studies had a mean follow-up of 2.7 years reporting on a total of 2012 participants. Most findings were based on single studies of moderate quality evidence. Risk factors increasing apathy onset were: being a carrier of the T allele of the PRND gene polymorphism, and having high levels of the IL-6 and TNFα cytokines at baseline. Risk factors for apathy worsening were: reduced inferior-temporal cortical thickness, taking antidepressants, being an ApoE ε4 carrier, living longer with AD, lower cognitive test scores, higher baseline apathy, premorbid personality traits (lower agreeableness, higher neuroticism), and higher midlife motivational abilities. CONCLUSIONS: Although results are limited by the small number of studies, this review identified specific genetic, neurobiological, AD specific, and dispositional factors that may increase risk of apathy onset and worsening in AD

Minor and subthreshold depressive disorders in Alzheimer's disease: a systematic review and meta-analysis of prevalence studies

Background: Depressive symptoms are common in Alzheimer's disease (AD) and negatively impact patient well-being. The main aim of the present study was to establish summary estimates for the prevalence of minor depressive disorder (MinD) and subthreshold depression in AD and synthesise evidence on prognosis and management of these symptoms in order to inform clinical guidelines. / Methods: Systematic review and meta-analysis of cross-sectional and longitudinal studies of prevalence, prognosis, and treatments for minor and subthreshold depression in AD. We searched MEDLINE, Embase, PsycINFO and CINAHL. We included studies that reported prevalence of subthreshold depressive disorders and those reporting data on validity of diagnostic criteria, mechanisms, or randomised controlled clinical trials (RCTs) testing effectiveness of interventions. Estimates of prevalence were pooled using random-effects meta-analyses. Two authors screened articles and independently extracted data on study characteristics. / Results: We reviewed 5671 abstracts, retrieved 621 full text articles and included a total of 15 studies. Pooling data from 10 studies showed that prevalence for MinD in AD was 22.0% (95% CI 16.0 to 28.0). Prevalence for a clinical diagnosis of MinD (DSM-III-R and DSM-IV) was 26.0% (95% CI 20.0 to 32.0; 6 studies). People with MinD experienced higher levels of neuropsychiatric symptoms, functional and cognitive decline, although studies remain cross-sectional. Neither sertraline nor a carer intervention were effective in reducing symptoms. / Conclusion: This review finds that MinD is prevalent in people with a diagnosis of AD and requires clinical attention. Research is warranted to develop effective interventions to treat and prevent these symptoms