Identification of characteristics that determine behavioral and personality changes in adult glioma patients

2021 ◽  
Author(s):  
Hanneke Zwinkels ◽  
Linda Dirven ◽  
Helen J Bulbeck ◽  
Robin Grant ◽  
Esther J J Habets ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Personality Traits ◽  
Brain Tumour ◽  
Online Survey ◽  
Clear Definition ◽  
Personality Changes ◽  
Definition Of ◽  
Different Characteristics ◽  
Adult Glioma

Abstract Background Glioma patients may experience behavioral and personality changes (BPC), negatively impacting their lives and that of their relatives. However, there is no clear definition of BPC for adult glioma patients, and here we aimed to determine which characteristics of BPC are relevant to include in this definition. Methods Possible characteristics of BPC were identified in the literature, and presented to patients and (former) caregivers in an online survey launched via the International Brain Tumour Alliance. Participants indicated the relevance for each characteristic, the three characteristics with most impact on their life, and missing characteristics. A cluster analysis and discussions with experts provided input to categorize characteristics and propose a definition for BPC. Results Completed surveys were obtained from 140 respondents; 35% patients, 50% caregivers and 15% unknown. Of 49 proposed characteristics, 35 were reported as relevant by at least 25% (range:7-44%) of respondents. Patients and caregivers rated different characteristics as most important. Common characteristics included in the top 10 of both patients and caregivers were lack of motivation, change in being socially active, not able to finish things and change in level of irritation. No characteristics were reported missing by ≥5 respondents. Three categories of BPC were identified: (1) emotions, needs and impulses (2) personality traits, and (3) poor judgement abilities. Conclusion The work resulted in a proposed definition for BPC in glioma patients, for which endorsement from the neuro-oncological community will besought. A next step is to identify or develop an instrument to evaluate BPC in glioma patients.

scholarly journals QOLP-23. IDENTIFICATION OF CHARACTERISTICS THAT DETERMINE BEHAVIORAL AND PERSONALITY CHANGES IN GLIOMA PATIENTS

2019 ◽  
Vol 21 (Supplement_6) ◽  
pp. vi202-vi202
Author(s):  
Hanneke Zwinkels ◽  
Linda Dirven ◽  
Helen Bulbeck ◽  
Robin Grant ◽  
Ingela Oberg ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Online Survey ◽  
Negative Impact ◽  
Daily Life ◽  
Assessment Tools ◽  
Clear Definition ◽  
Tumor Patients ◽  
Personality Changes ◽  
Grade Ii ◽  
Different Characteristics

Abstract BACKGROUND Glioma patients may experience behavioral and personality changes (BPC), which have a negative impact on the lives of both brain tumor patients and their relatives. The extent of BPC is currently unknown, and it is unclear if available assessment tools cover all aspects of BPC that are relevant for glioma patients. This study aimed to determine which characteristics of BPC are relevant for glioma patients. METHODS Possible characteristics of BPC were identified in the literature and based on expert opinion. Next, these 49 items were presented to patients and caregivers/former caregivers in an online survey launched via the International Brain Tumour Alliance. Participants were requested to indicate the relevance for each characteristic on a 4-point Likert scale ranging from ‘not at all’ to ‘very much’. In addition, they had to indicate which three characteristics had most impact on their daily life, and if characteristics were missing. RESULTS Completed surveys were obtained from 141 respondents, of which 36% were patients, 50% caregivers and 14% unknown. Most patients had grade II or IV glioma (29% vs 38%). Of 49 characteristics, 35 were reported as relevant in at least 25% (range all characteristics: 7–44%). Patients (n=50) and caregivers (n=70) rated different characteristics as most important. Common characteristics were lack of motivation, change in being socially active, not able to finish things and change in level of irritation. There were no characteristics reported to be missing by ≥5 respondents. CONCLUSION The majority of characteristics were rated as relevant in >25% of respondents, and patients and caregivers differed in which were most relevant. A clear definition based on these results is therefore difficult to establish. A next step would be to perform a cluster analysis of patients and caregivers separately, and discuss the results with experts, to reach consensus on an appropriate definition.

The Influence of Personality Traits among Ordinary, Problematic and Addicted Facebook Users. A Study on University Students in India.

2019 ◽  
Author(s):  
Thipparapu Rajesh ◽  
B Rangaiah
Keyword(s):  
Cluster Analysis ◽  
University Students ◽  
Personality Traits ◽  
Online Survey ◽  
Survey Methods ◽  
Openness To Experience ◽  
Indian Context ◽  
Facebook Addiction ◽  
Future Direction

Personality traits are important factors in determining online behaviors. The association between personality traits and Facebook addiction in the Indian context is still unexplored. This study sought to examine the influence of personality traits on Facebook addiction. A sample of 348 Facebook users has participated in offline and online survey methods. The sample was divided into ordinary, problematic and addicted Facebook users by using k means cluster analysis. The results of our study showed that extraversion, conscientiousness, openness to experience and loneliness have differed among ordinary, problematic and addicted Facebook users. Agreeableness, openness to experience were negatively related to Facebook addiction. Loneliness and narcissism were positively associated with Facebook addiction. The limitations and future direction were discussed.

Classification of Observations through Combination of the Dimension Reduction and the Cluster Analysis

2017 ◽  
Vol 7 (8) ◽  
pp. 30
Author(s):  
Hyeuk Kim
Keyword(s):  
Machine Learning ◽  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Unsupervised Learning ◽  
Principal Component ◽  
Component Analysis ◽  
Baseball Players ◽  
Partitioning Around Medoids ◽  
Different Characteristics

Unsupervised learning in machine learning divides data into several groups. The observations in the same group have similar characteristics and the observations in the different groups have the different characteristics. In the paper, we classify data by partitioning around medoids which have some advantages over the k-means clustering. We apply it to baseball players in Korea Baseball League. We also apply the principal component analysis to data and draw the graph using two components for axis. We interpret the meaning of the clustering graphically through the procedure. The combination of the partitioning around medoids and the principal component analysis can be used to any other data and the approach makes us to figure out the characteristics easily.

Gender and Organizational Conflict Management: The Mediating Role of Personality

2018 ◽  
Author(s):  
Maciej Kościelniak ◽  
Jarosław Piotrowski ◽  
Magdalena Żemojtel-Piotrowska
Keyword(s):  
Conflict Management ◽  
Personality Traits ◽  
Structural Equation ◽  
Online Survey ◽  
Conflict Behavior ◽  
Equation Modeling ◽  
Conflict Management Styles ◽  
Mediating Role ◽  
Big Five Model

Many authors examined the interplay between gender and conflict management preferences, but those findings were often mixed and inconsistent. In the current paper we tried to explain those inconsistencies by investigating the mediating role of personality for the relationship of gender and conflict management. Rahim's inventory was used for identifying five conflict management styles, and Big Five Model theory was a base for assessing participants' personality traits. Data were collected from a sample of 1,055 working Poles (52.7% women), in an online survey. Based on the structural equation modeling we detected multiple indirect mediating paths of gender on conflict management via personality traits, while no direct effect of gender was observed. Despite some limitations, the study sheds light on the actual role of gender in conflict behavior and the importance of personality traits in the conflict management, both from a theoretical and practical perspective.

The first flush in sewer systems

1996 ◽  
Vol 33 (9) ◽  
pp. 101-108 ◽  
Author(s):  
Agnès Saget ◽  
Ghassan Chebbo ◽  
Jean-Luc Bertrand-Krajewski
Keyword(s):  
Treatment Strategy ◽  
Real Data ◽  
First Flush ◽  
Clear Definition ◽  
Controversial Subject ◽  
Sewer Systems ◽  
Wet Weather ◽  
Definition Of ◽  
Appearance Frequency

The first flush phenomenon of urban wet weather discharges is presently a controversial subject. Scientists do not agree with its reality, nor with its influences on the size of treatment works. Those disagreements mainly result from the unclear definition of the phenomenon. The objective of this article is first to provide a simple and clear definition of the first flush and then to apply it to real data and to obtain results about its appearance frequency. The data originate from the French database based on the quality of urban wet weather discharges. We use 80 events from 7 separately sewered basins, and 117 events from 7 combined sewered basins. The main result is that the first flush phenomenon is very scarce, anyway too scarce to be used to elaborate a treatment strategy against pollution generated by urban wet weather discharges.

Attitudes of Medical Workers Toward Artificial Intelligence in Ophthalmology: A Comparative Survey (Preprint)

2020 ◽  
Author(s):  
Weihua Yang ◽  
Bo Zheng ◽  
Maonian Wu ◽  
Shaojun Zhu ◽  
Hongxia Zhou ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Medical Ethics ◽  
Online Survey ◽  
Medical Professionals ◽  
Medical Field ◽  
Acceptance Level ◽  
Professional Workers ◽  
Basic Understanding ◽  
Comparative Survey ◽  
Definition Of

BACKGROUND Artificial intelligence (AI) is widely applied in the medical field, especially in ophthalmology. In the development of ophthalmic artificial intelligence, some problems worthy of attention have gradually emerged, among which the ophthalmic AI-related recognition issues are particularly prominent. That is to say, currently, there is a lack of research into people's familiarity with and their attitudes toward ophthalmic AI. OBJECTIVE This survey aims to assess medical workers’ and other professional technicians’ familiarity with AI, as well as their attitudes toward and concerns of ophthalmic AI. METHODS An electronic questionnaire was designed through the Questionnaire Star APP, an online survey software and questionnaire tool, and was sent to relevant professional workers through Wechat, China’s version of Facebook or WhatsApp. The participation was based on a voluntary and anonymous principle. The questionnaire mainly consisted of four parts, namely the participant’s background, the participant's basic understanding of AI, the participant's attitude toward AI, and the participant's concerns about AI. A total of 562 participants were counted, with 562 valid questionnaires returned. The results of the questionnaires are displayed in an Excel 2003 form. RESULTS A total of 562 professional workers completed the questionnaire, of whom 291 were medical workers and 271 were other professional technicians. About 37.9% of the participants understood AI, and 31.67% understood ophthalmic AI. The percentages of people who understood ophthalmic AI among medical workers and other professional technicians were about 42.61% and 15.6%, respectively. About 66.01% of the participants thought that ophthalmic AI would partly replace doctors, with about 59.07% still having a relatively high acceptance level of ophthalmic AI. Meanwhile, among those with ophthalmic AI application experiences (30.6%), respectively about 84.25% of medical professionals and 73.33% of other professional technicians held a full acceptance attitude toward ophthalmic AI. The participants expressed concerns that ophthalmic AI might bring about issues such as the unclear definition of medical responsibilities, the difficulty of ensuring service quality, and the medical ethics risks. And among the medical workers and other professional technicians who understood ophthalmic AI, 98.39%, and 95.24%, respectively, said that there was a need to increase the study of medical ethics issues in the ophthalmic AI field. CONCLUSIONS Analysis of the questionnaire results shows that the medical workers have a higher understanding level of ophthalmic AI than other professional technicians, making it necessary to popularize ophthalmic AI education among other professional technicians. Most of the participants did not have any experience in ophthalmic AI, but generally had a relatively high acceptance level of ophthalmic AI, believing that doctors would partly be replaced by it and that there was a need to strengthen research into medical ethics issues of the field.

Systematic Literature Review on Smart Mobility: A Framework for Future “Quantitative” Developments

2021 ◽  
pp. 088541222199424
Author(s):  
Mauro Francini ◽  
Lucia Chieffallo ◽  
Annunziata Palermo ◽  
Maria Francesca Viapiana
Keyword(s):  
Cluster Analysis ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Performance Indicators ◽  
State Of The Art ◽  
Measurement Model ◽  
Broader Impacts ◽  
Research Goal ◽  
Smart Mobility ◽  
Definition Of

This work aims to reorganize theoretical and empirical research on smart mobility through the systematic literature review approach. The research goal is to reach an extended and shared definition of smart mobility using the cluster analysis. The article provides a summary of the state of the art that can have broader impacts in determining new angles for approaching research. In particular, the results will be a reference for future quantitative developments for the authors who are working on the construction of a territorial measurement model of the smartness degree, helping them in identifying performance indicators consistent with the definition proposed.

scholarly journals SIMULTANEOUS DEFINITION OF KEY CHARACTERISTICS IN ORDER TO FACILITATE ROBUST DESIGN IN EARLY PRODUCT DEVELOPMENT STAGES

2021 ◽  
Vol 1 ◽  
pp. 2691-2700
Author(s):  
Stefan Goetz ◽  
Dennis Horber ◽  
Benjamin Schleich ◽  
Sandro Wartzack
Keyword(s):  
Product Development ◽  
Robust Design ◽  
Language Processing ◽  
Design Stage ◽  
Concept Design ◽  
Clear Definition ◽  
Implicit Information ◽  
Key Characteristics ◽  
Associated Functions ◽  
Definition Of

AbstractThe success of complex product development projects strongly depends on the clear definition of target factors that allow a reliable statement about the fulfilment of the product requirements. In the context of tolerancing and robust design, Key Characteristics (KCs) have been established for this purpose and form the basis for all downstream activities. In order to integrate the activities related to the KC definition into product development as early as possible, the often vaguely formulated requirements must be translated into quantifiable KCs. However, this is primarily a manual process, so the results strongly depend on the experience of the design engineer.In order to overcome this problem, a novel computer-aided approach is presented, which automatically derives associated functions and KCs already during the definition of product requirements. The approach uses natural language processing and formalized design knowledge to extract and provide implicit information from the requirements. This leads to a clear definition of the requirements and KCs and thus creates a founded basis for robustness evaluation at the beginning of the concept design stage. The approach is exemplarily applied to a window lifter.

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