Social Network Characteristics Impact Long-Term Drinking Outcomes

Background: Relationships are vital to recovery however, there is uncertainty whether users have different types of social networks in different mental health settings and how these networks may impact on users’ wellbeing. Aims: To compare the social networks of people with long-term mental illness in the community with those of people in a general adult in-patient unit. Method: A sample of general adult in-patients with enduring mental health problems, aged between 18 and 65, was compared with a similar sample attending a general adult psychiatric clinic. A cross-sectional survey collected demographic data and information about participants’ social networks. Participants also completed the Short Warwick Edinburgh Mental Well-Being Scale to examine well-being and the Significant Others Scale to explore their social network support. Results: The study recruited 53 participants (25 living in the community and 28 current in-patients) with 339 named as important members of their social networks. Both groups recorded low numbers in their social networks though the community sample had a significantly greater number of social contacts (7.4 vs. 5.4), more monthly contacts with members of their network and significantly higher levels of social media use. The in-patient group reported greater levels of emotional and practical support from their network. Conclusions: People with serious and enduring mental health problems living in the community had a significantly greater number of people in their social network than those who were in-patients while the in-patient group reported greater levels of emotional and practical support from their network. Recommendations for future work have been made.

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35 Social Contact Mode and 15-Year Episodic Memory Trajectories in Older Adults with and Without Hearing Loss: the Elsa Study

Age and Ageing ◽

10.1093/ageing/afab029.14 ◽

2021 ◽

Vol 50 (Supplement_1) ◽

pp. i7-i11

Author(s):

S Rafnsson ◽

A Maharani ◽

G Tampubolon

Keyword(s):

Older Adults ◽

Hearing Loss ◽

Social Network ◽

Episodic Memory ◽

Social Interactions ◽

Social Contact ◽

Sensitivity Analyses ◽

Impaired Hearing ◽

Contact Mode

Abstract Introduction Frequent social contact benefits cognition in later life although evidence is lacking on the potential importance of the modes chosen by older adults for interacting with others in their social network. Method 11,513 participants in the English Longitudinal Study of Ageing (ELSA) provided baseline information on hearing status and social contact mode and frequency of use. Multilevel growth curve models compared episodic memory (immediate and delayed recall) at baseline and long-term in participants who interacted frequently (offline only or offline and online combined), compared to infrequently, with others in their social network. Results Frequent offline (β = 0.29; p < 0.05) and combined offline and online (β = 0.76; p < 0.001) social interactions predicted better episodic memory after adjustment for multiple confounding factors. We observed positive long-term influences of combined offline and online interactions on memory in participants without hearing loss (β = 0.48, p = 0.001) but not of strictly offline interactions (β = 0.00, p = 0.970). In those with impaired hearing, long-term memory was positively influenced by both modes of engagement (offline only: β = 0.93, p < 0.001; combined online and offline: β = 1.47, p < 0.001). Sensitivity analyses confirmed the robustness of these findings. Conclusion Supplementing conventional social interactions with online communication modes may help older adults, especially those living with hearing loss, sustain, and benefit cognitively from, personal relationships.

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Relationships between medical students’ co-regulatory network characteristics and self-regulated learning: a social network study

Perspectives on Medical Education ◽

10.1007/s40037-021-00664-x ◽

2021 ◽

Author(s):

Derk Bransen ◽

Marjan J. B. Govaerts ◽

Dominique M. A. Sluijsmans ◽

Jeroen Donkers ◽

Piet G. C. Van den Bossche ◽

...

Keyword(s):

Social Network ◽

Medical Students ◽

Regulatory Network ◽

Regulatory Networks ◽

Learning Opportunities ◽

Network Size ◽

Tie Strength ◽

Network Characteristics ◽

Self Regulated Learning ◽

Regulated Learning

Abstract Introduction Recent conceptualizations of self-regulated learning acknowledge the importance of co-regulation, i.e., students’ interactions with others in their networks to support self-regulation. Using a social network approach, the aim of this study is to explore relationships between characteristics of medical students’ co-regulatory networks, perceived learning opportunities, and self-regulated learning. Methods The authors surveyed 403 undergraduate medical students during their clinical clerkships (response rate 65.5%). Using multiple regression analysis, structural equation modelling techniques, and analysis of variance, the authors explored relationships between co-regulatory network characteristics (network size, network diversity, and interaction frequency), students’ perceptions of learning opportunities in the workplace setting, and self-reported self-regulated learning. Results Across all clerkships, data showed positive relationships between tie strength and self-regulated learning (β = 0.095, p < 0.05) and between network size and tie strength (β = 0.530, p < 0.001), and a negative relationship between network diversity and tie strength (β = −0.474, p < 0.001). Students’ perceptions of learning opportunities showed positive relationships with both self-regulated learning (β = 0.295, p < 0.001) and co-regulatory network size (β = 0.134, p < 0.01). Characteristics of clerkship contexts influenced both co-regulatory network characteristics (size and tie strength) and relationships between network characteristics, self-regulated learning, and students’ perceptions of learning opportunities. Discussion The present study reinforces the importance of co-regulatory networks for medical students’ self-regulated learning during clinical clerkships. Findings imply that supporting development of strong networks aimed at frequent co-regulatory interactions may enhance medical students’ self-regulated learning in challenging clinical learning environments. Social network approaches offer promising ways of further understanding and conceptualising self- and co-regulated learning in clinical workplaces.

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Social network characteristics moderate associations between cortical thickness and cognitive functioning in older adults

Alzheimer s & Dementia ◽

10.1002/alz.12383 ◽

2021 ◽

Author(s):

Neika Sharifian ◽

Afsara B. Zaheed ◽

Emily P. Morris ◽

Ketlyne Sol ◽

Jennifer J. Manly ◽

...

Keyword(s):

Older Adults ◽

Social Network ◽

Cognitive Functioning ◽

Cortical Thickness ◽

Network Characteristics

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Social Networks and Loneliness During the COVID-19 Pandemic

Socius Sociological Research for a Dynamic World ◽

10.1177/2378023120985254 ◽

2021 ◽

Vol 7 ◽

pp. 237802312098525

Author(s):

Balazs Kovacs ◽

Nicholas Caplan ◽

Samuel Grob ◽

Marissa King

Keyword(s):

Social Network ◽

Social Isolation ◽

Close Relationships ◽

Network Size ◽

Global Network ◽

Network Data ◽

Network Characteristics ◽

Face To Face ◽

Social Network Data ◽

Social Network Size

We utilize longitudinal social network data collected pre–COVID-19 in June 2019 and compare them with data collected in the midst of COVID in June 2020. We find significant decreases in network density and global network size following a period of profound social isolation. While there is an overall increase in loneliness during this era, certain social network characteristics of individuals are associated with smaller increases in loneliness. Specifically, we find that people with fewer than five “very close” relationships report increases in loneliness. We further find that face-to-face interactions, as well as the duration and frequency of interactions with very close ties, are associated with smaller increases in loneliness during the pandemic. We also report on factors that do not moderate the effect of social isolation on perceived loneliness, such as gender, age, or overall social network size.

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Identifying Project Corporate Behavioral Risks to Support Long-Term Sustainable Cooperative Partnerships

Sustainability ◽

10.3390/su13116347 ◽

2021 ◽

Vol 13 (11) ◽

pp. 6347

Author(s):

Marco Nunes ◽

António Abreu ◽

Célia Saraiva

Keyword(s):

Social Network ◽

Project Management ◽

Social Network Analysis ◽

Network Analysis ◽

Building Blocks ◽

Research Literature ◽

Management Tools ◽

Dynamic Interactions ◽

Major Factors

Projects are considered crucial building blocks whereby organizations execute and implement their short-, mid-, and long-term strategic visions. Projects are thought, developed, and implemented to solve problems, drive change, satisfy unique needs, add value, and exploit opportunities, just to name a few objectives. Although existing project management tools and techniques aim to deliver projects with success, according to the latest reviewed literature, projects still keep failing at an impressive pace. Among the extensive list of factors that may threaten project success, several articles from the research literature place particular importance on a still underexplored factor that may strongly lead to unsuccessful project delivery. This factor—usually known as corporate behavioral risks—usually emerges and evolves as organizations work together to deliver projects across a bounded period of time, and is characterized by the mix of formal and informal dynamic interactions between the different stakeholders that constitute the different organizations. Furthermore, several articles from the research literature also point out the lack of proper models to efficiently manage corporate behavioral risks as one of the major factors that may lead to projects failing. To efficiently identify and measure how such corporate behaviors may contribute to a project’s outcomes (success or failure), a heuristic model is proposed in this work, developed based on four fundamental fields ((1) project management, (2) risk management, (3) corporate behavior, and (4) social network analysis), to quantitatively analyze four critical project social networks ((1) communication, (2) problem-solving, (3) advice, and (4) trust), by applying the theory of social network analysis (SNA). The proposed model in this work is supported with a case study to illustrate its implementation and application across a project lifecycle, and how organizations can benefit from its application.

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