scholarly journals Future research avenues to facilitate social connectedness and safe collective behavior at organized crowd events

2021 ◽  
Vol 24 (2) ◽  
pp. 216-222
Author(s):  
Anne Templeton
Keyword(s):  
Social Connectedness ◽  
Extreme Case ◽  
Group Processes ◽  
Future Research ◽  
Collective Behaviors ◽  
Accurate Perception ◽  
Working Together ◽  
Future Research Directions ◽  
Crowd Psychology ◽  
Perception Of Health

During the COVID-19 pandemic, organizers of crowd events must facilitate physical distancing in environments where attendees previously enjoyed being close with ingroup members, encourage accurate perception of health risks and close adherence to safety guidance, and stop expected normative behaviors that may now be unsafe. Research from crowd psychology demonstrates how group processes are integral to each of these issues. The COVID-19 pandemic, however, has created an extreme case environment in which to evaluate the collective findings from previous research and identify future research directions. This paper outlines how organizers of crowd events and researchers can work together to further develop our understanding of social connectedness in crowds, reasons for risk-taking behavior, and level of engagement in new collective behaviors. By working together to address these issues, practitioners and researchers can develop our understanding of crowd processes and improve safety at future crowd events.

scholarly journals Group Positive Affect and Beyond: An Integrative Review and Future Research Agenda

2020 ◽  
Vol 17 (20) ◽  
pp. 7499
Author(s):  
Jonathan Peñalver ◽  
Marisa Salanova ◽  
Isabel M. Martínez
Keyword(s):  
Positive Affect ◽  
Research Agenda ◽  
Group Processes ◽  
Integrative Review ◽  
Future Research ◽  
Future Research Agenda ◽  
Similarity Group ◽  
Working Together ◽  
And Performance ◽  
The Individual

Group positive affect is defined as homogeneous positive affect among group members that emerges when working together. Considering that previous research has shown a significant relationship between group positive affect and a wide variety of group outcomes (e.g., behaviors, wellbeing, and performance), it is crucial to boost our knowledge about this construct in the work context. The main purpose is to review empirical research, to synthesize the findings and to provide research agenda about group positive affect, in order to better understand this construct. Through the PsycNET and Proquest Central databases, an integrative review was conducted to identify articles about group positive affect published between January 1990 and March 2019. A total of 44 articles were included and analyzed. Finding suggests that scholars have been more interested in understanding the outcomes of group positive affect and how to improve the productivity of groups than in knowing what the antecedents are. A summary conclusion is that group positive affect is related to leadership, job demands, job resources, diversity/similarity, group processes, and contextual factors, all of which influence the development of several outcomes and different types of wellbeing at the individual and group levels. However, with specific combinations of other conditions (e.g., group trust, negative affect, and interaction), high levels of group positive affect could cause harmful results. Conclusions shed light on group positive affect research and practice and might help Human Resources professionals to initiate empirically-based strategies related to recruitment, group design and leadership training.

Applying CI in Biology through PSO

2020 ◽  
pp. 502-527
Author(s):  
Rojalina Priyadarshini ◽  
Nilamadhab Dash ◽  
Brojo Kishore Mishra ◽  
Rachita Misra
Keyword(s):  
Optimization Problems ◽  
Real Life ◽  
Population Based ◽  
Computing Methods ◽  
Future Research ◽  
Natural Systems ◽  
Solution Methods ◽  
Working Together ◽  
Future Research Directions ◽  
Population Based Algorithm

Conventional computing methods face challenges dealing with real world problems, which are characterised by noisy or incomplete data. To find solutions for such problems, natural systems have evolved over the years and on analysis it has been found these contain many simple elements when working together to solve real life complex problems. Swarm Intelligence (SI) is one of the techniques which is inspired by nature and is a population based algorithm motivated by the collective behaviour of a group of social insects. Particle swarm optimization (PSO) is one of the techniques belonging to this group, used to solve some optimization problems. This chapter will discuss some of the problems existing in computational biology, their contemporary solution methods followed by the use of PSO to address those problems. Along with this several applications of PSO are discussed in few of the relevant fields are discussed having some future research directions on this field.

Applying CI in Biology through PSO

2016 ◽  
pp. 119-143
Author(s):  
Rojalina Priyadarshini ◽  
Nilamadhab Dash ◽  
Brojo Kishore Mishra ◽  
Rachita Misra
Keyword(s):  
Optimization Problems ◽  
Real Life ◽  
Population Based ◽  
Computing Methods ◽  
Future Research ◽  
Natural Systems ◽  
Solution Methods ◽  
Working Together ◽  
Future Research Directions ◽  
Population Based Algorithm

Conventional computing methods face challenges dealing with real world problems, which are characterised by noisy or incomplete data. To find solutions for such problems, natural systems have evolved over the years and on analysis it has been found these contain many simple elements when working together to solve real life complex problems. Swarm Intelligence (SI) is one of the techniques which is inspired by nature and is a population based algorithm motivated by the collective behaviour of a group of social insects. Particle swarm optimization (PSO) is one of the techniques belonging to this group, used to solve some optimization problems. This chapter will discuss some of the problems existing in computational biology, their contemporary solution methods followed by the use of PSO to address those problems. Along with this several applications of PSO are discussed in few of the relevant fields are discussed having some future research directions on this field.

Self-Compassion and Quality of Life in Adults Who Stutter

2020 ◽  
Vol 29 (4) ◽  
pp. 2097-2108
Author(s):  
Robyn L. Croft ◽  
Courtney T. Byrd
Keyword(s):  
Quality Of Life ◽  
Social Connectedness ◽  
The Self ◽  
Future Research ◽  
Self Compassion ◽  
Adults Who Stutter ◽  
And Gender ◽  
Relationship Of ◽  
The Impact

Purpose The purpose of this study was to identify levels of self-compassion in adults who do and do not stutter and to determine whether self-compassion predicts the impact of stuttering on quality of life in adults who stutter. Method Participants included 140 adults who do and do not stutter matched for age and gender. All participants completed the Self-Compassion Scale. Adults who stutter also completed the Overall Assessment of the Speaker's Experience of Stuttering. Data were analyzed for self-compassion differences between and within adults who do and do not stutter and to predict self-compassion on quality of life in adults who stutter. Results Adults who do and do not stutter exhibited no significant differences in total self-compassion, regardless of participant gender. A simple linear regression of the total self-compassion score and total Overall Assessment of the Speaker's Experience of Stuttering score showed a significant, negative linear relationship of self-compassion predicting the impact of stuttering on quality of life. Conclusions Data suggest that higher levels of self-kindness, mindfulness, and social connectedness (i.e., self-compassion) are related to reduced negative reactions to stuttering, an increased participation in daily communication situations, and an improved overall quality of life. Future research should replicate current findings and identify moderators of the self-compassion–quality of life relationship.

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