scholarly journals Pre-sleep arousal and fear of sleep in trauma-related sleep disturbances: A cluster-analytic approach

2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Gabriela G. Werner ◽  
Sarah K. Danböck ◽  
Stanislav Metodiev ◽  
Anna E. Kunze
Keyword(s):  
Cluster Analysis ◽  
Hierarchical Cluster Analysis ◽  
Sleep Disturbances ◽  
Hierarchical Cluster ◽  
Cluster Solution ◽  
Treatment Target ◽  
Online Study ◽  
Sleep Arousal ◽  
Cluster Analytic ◽  
Post Hoc

Background Trauma-related sleep disturbances constitute critical symptoms of posttraumatic stress disorder (PTSD), but sleep symptoms often reside even after successful trauma-focused psychotherapy. Therefore, currently unattended factors – like fear of sleep (FoS) – might play a crucial role in the development and maintenance of residual sleep disturbances. However, it is unclear whether trauma-exposed individuals exhibit different symptomatic profiles of sleep disturbances that could inform individualized therapeutic approaches and eventually enhance treatment efficacy. Method In a large online study, a two-step cluster analysis and a hierarchical cluster analysis using Ward’s method were performed to explore subgroups among trauma-exposed individuals (N = 471) in terms of FoS, different aspects of trauma-related sleep disturbances (e.g., insomnia symptoms, nightmares, arousal), and PTSD symptoms. These variables were compared between resulting clusters using ANOVAs and Scheffé’s post-hoc tests. Results The hierarchical cluster analysis supported 3- and 4-cluster solutions. The 3-cluster solution consisted of one “healthy” (n = 199), one “subclinical” (n = 223), and one “clinical” (n = 49) cluster, with overall low, medium, and high symptomatology on all used variables. In the 4-cluster solution, the clinical cluster was further divided into two subgroups (n = 38, n = 11), where one cluster was specifically characterized by elevated somatic pre-sleep arousal and high levels of FoS. Conclusions A subgroup of trauma-exposed individuals with PTSD and sleep disturbances suffers from increased pre-sleep arousal and FoS, which has been suggested as one possible explanation for residual sleep disturbances. In these patients, FoS might be a relevant treatment target.

scholarly journals Segmenting Inbound Tourists Using Destination Image

Tourism ◽  
2021 ◽  
Vol 69 (1) ◽  
pp. 47-57
Author(s):  
Dev Jani
Keyword(s):  
Cluster Analysis ◽  
Hierarchical Cluster Analysis ◽  
Travel Behavior ◽  
Statistical Significance ◽  
Hierarchical Cluster ◽  
Destination Image ◽  
Cluster Solution ◽  
Multiple Choice Questions ◽  
Chi Square ◽  
African Context

The purpose of this study was to segment inbound tourists to Tanzania using destination image. A self-administered structured questionnaire was conveniently distributed to inbound tourist to Tanzania in two major international airports in Tanzania. The questionnaire captured destination image using a five point Likert type scale while the demographics, sources of travel information, and travel behavior were captured using dichotomy or multiple choice questions. A total of 625 dully filled questionnaires were used for data analysis. A factor-cluster analysis was used in analyzing the data, with factor analysis serving in reducing the items into few dimensions that were subsequently subjected to stepwise cluster analysis. A hierarchical cluster analysis was used to explore the possible numbers of clusters followed by hierarchical cluster analysis (k-means) that confirmed the appropriate number of clusters. A three cluster solution was obtained with follow up one way ANOVA, t-tests, and Chi-square indicating statistical significance differences between the clusters basing on travel motives and travel behavior. The findings offer practical implications to destination managers on the use of destination image in marketing destinations to different tourist segments. This study explored the possible tourist segments basing on destination image of less researched African context.

Prejudice, Social Dominance, and Similarity among People who Favor Integration of Minorities

2016 ◽  
Vol 19 ◽  
Author(s):  
Carmen Martínez ◽  
José Saiz ◽  
Josefa Angosto
Keyword(s):  
Cluster Analysis ◽  
Effect Size ◽  
Hierarchical Cluster Analysis ◽  
Social Dominance ◽  
Hierarchical Cluster ◽  
Cluster Solution ◽  
Perceived Similarity ◽  
Latin Americans

AbstractThis study examines differences in prejudice, perceived similarity, and social dominance in members of the majority who favor integration as a means of minority acculturation. A total of 342 non-Gypsy Spanish participants filled out a questionnaire about their relationship to one of three outgroups: Maghrebians, Gypsies, and Latin Americans. Hierarchical cluster analysis showed that a three-cluster solution was most fitting for every outgroup. ANOVAs applied to the three clusters indicated significant differences in prejudice, perceived similarity, and social dominance. Referring to Gypsies the largest effect size was observed in manifest prejudice (η2= .63), in Maghrebians, the largest effect size was observed in subtle prejudice (η2=.77), while for Latin Americans, perceived similarity had the largest effect size η2( = .60). The results reveal a need to modify existing measures of integration; we recommend using questionnaires to measure behaviors that members of the majority would be willing to implement.

Extraordinary circumstances: Covid-19 – Italian Serie A scenario

2021 ◽  
pp. 175433712110192
Author(s):  
Milan Radojicic ◽  
Aleksandar Djokovic ◽  
Nikola Cvetkovic
Keyword(s):  
Cluster Analysis ◽  
Hierarchical Cluster Analysis ◽  
Hierarchical Cluster ◽  
Round Robin ◽  
The Past ◽  
Novel Approach ◽  
Round Robin Tournaments

Unpredictable and uncontrollable situations have happened throughout history. Inevitably, such situations have an impact on various spheres of life. The coronavirus disease 2019 has affected many of them, including sports. The ban on social gatherings has caused the cancellation of many sports competitions. This paper proposes a methodology based on hierarchical cluster analysis (HCA) that can be applied when a need occurs to end an interrupted tournament and the conditions for playing the remaining matches are far from ideal. The proposed methodology is based on how to conclude the season for Serie A, a top-division football league in Italy. The analysis showed that it is reasonable to play 14 instead of the 124 remaining matches of the 2019–2020 season to conclude the championship. The proposed methodology was tested on the past 10 seasons of the Serie A, and its effectiveness was confirmed. This novel approach can be used in any other sport where round-robin tournaments exist.

scholarly journals Detection of drought events in Greece using daily precipitation

2010 ◽  
Vol 41 (2) ◽  
pp. 126-133 ◽  
Author(s):  
N. Kalamaras ◽  
H. Michalopoulou ◽  
H. R. Byun
Keyword(s):  
Cluster Analysis ◽  
Hierarchical Cluster Analysis ◽  
Daily Precipitation ◽  
Hierarchical Cluster ◽  
Seasonal Distribution ◽  
Drought Severity ◽  
Severe Drought ◽  
Analysis Method ◽  
Cluster Analysis Method ◽  
Insight Into

In this study a method proposed by Byun & Wilhite, which estimates drought severity and duration using daily precipitation values, is applied to data from stations at different locations in Greece. Subsequently, a series of indices is calculated to facilitate the detection of drought events at these sites. The results provide insight into the trend of drought severity in the region. In addition, the seasonal distribution of days with moderate and severe drought is examined. Finally, the Hierarchical Cluster Analysis method is used to identify sites with similar drought features.

An investigation on conceptual understanding about cosmology

2019 ◽  
Vol 15 (S367) ◽  
pp. 397-399
Author(s):  
Arturo Colantonio ◽  
Irene Marzoli ◽  
Italo Testa ◽  
Emanuella Puddu
Keyword(s):  
High School ◽  
Cluster Analysis ◽  
High School Students ◽  
Conceptual Understanding ◽  
Hierarchical Cluster Analysis ◽  
Hierarchical Cluster ◽  
Content Area ◽  
School Students ◽  
Convenience Sample ◽  
Teaching Activities

AbstractIn this study, we identify patterns among students beliefs and ideas in cosmology, in order to frame meaningful and more effective teaching activities in this amazing content area. We involve a convenience sample of 432 high school students. We analyze students’ responses to an open-ended questionnaire with a non-hierarchical cluster analysis using the k-means algorithm.

Hierarchical Cluster Analysis Identifies Distinct Physiological States After Acute Brain Injury

2021 ◽  
Author(s):  
Swarna Rajagopalan ◽  
Wesley Baker ◽  
Elizabeth Mahanna-Gabrielli ◽  
Andrew William Kofke ◽  
Ramani Balu
Keyword(s):  
Cluster Analysis ◽  
Brain Injury ◽  
Hierarchical Cluster Analysis ◽  
Hierarchical Cluster ◽  
Acute Brain Injury
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