Professional advice for primary healthcare workers in Ethiopia: a social network analysis

Membership associations are vital to build social capital and networks among their members through the exchange of information and resources, roles especially valuable for emerging entrepreneurs. That is the case of associations catering to professionals in agritourism, an enterprise bringing farming and tourism together. However, whether the exchange of information and resources among members holds true within agritourism associations is yet to be known. Filling this knowledge gap is critical given the stated benefits agritourism delivers to society and farmers’ necessity to expand their business networks to increase entrepreneurial success. Therefore, this study evaluated the extent of social capital and networks within a prominent agritourism-focused association in North America. Data were collected from members using a web-based survey in 2016. Analyses included descriptive statistical tests and Social Network Analysis (SNA). Results showed high levels of social capital among members, especially related to its relational dimension (e.g., share professional advice), as well as strong bi-directional (to/from) trust, cooperation, and reciprocity among members. SNA indicated members were well connected and had a healthy information exchange, without the organization intervention. Study results are discussed to provide managerial intelligence towards strengthening social capital and networks within associations catering to agritourism and other niche-tourism professionals.

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Prioritizing Healthcare Worker Vaccinations on the Basis of Social Network Analysis

Infection Control and Hospital Epidemiology ◽

10.1086/655466 ◽

2010 ◽

Vol 31 (9) ◽

pp. 893-900 ◽

Cited By ~ 36

Author(s):

Philip M. Polgreen ◽

Troy Leo Tassier ◽

Sriram Venkata Pemmaraju ◽

Alberto Maria Segre

Keyword(s):

Social Network ◽

Social Network Analysis ◽

Network Analysis ◽

Healthcare Workers ◽

Computational Simulation ◽

Vaccination Strategy ◽

Occupational Therapists ◽

Agent Based ◽

X Ray ◽

Vaccination Rates

Objective.To use social network analysis to design more effective strategies for vaccinating healthcare workers against influenza.Design.An agent-based simulation.Setting.A simulation based on a 700-bed hospital.Methods.We first observed human contacts (defined as approach within approximately 0.9 m) performed by 15 categories of healthcare workers (eg, floor nurses, intensive care unit nurses, staff physicians, phlebotomists, and respiratory therapists). We then constructed a series of contact graphs to represent the social network of the hospital and used these graphs to run agent-based simulations to model the spread of influenza. A targeted vaccination strategy that preferentially vaccinated more “connected” healthcare workers was compared with other vaccination strategies during simulations with various base vaccination rates, vaccine effectiveness, probability of transmission, duration of infection, and patient length of stay.Results.We recorded 6,654 contacts by 148 workers during 606 hours of observations from January through December 2006. Unit clerks, X-ray technicians, residents and fellows, transporters, and physical and occupational therapists had the most contacts. When repeated contacts with the same individual were excluded, transporters, unit clerks, X-ray technicians, physical and occupational therapists, and social workers had the most contacts. Preferentially vaccinating healthcare workers in more connected job categories yielded a substantially lower attack rate and fewer infections than a random vaccination strategy for all simulation parameters.Conclusions.Social network models can be used to derive more effective vaccination policies, which are crucial during vaccine shortages or in facilities with low vaccination rates. Local vaccination priorities can be determined in any healthcare facility with only a modest investment in collection of observational data on different types of healthcare workers. Our findings and methods (ie, social network analysis and computational simulation) have implications for the design of effective interventions to control a broad range of healthcare-associated infections.

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Implementation of an interprofessional collaboration in practice program: a feasibility study using social network analysis

Pilot and Feasibility Studies ◽

10.1186/s40814-020-00746-3 ◽

2021 ◽

Vol 7 (1) ◽

Author(s):

Linda C. Smit ◽

Jeroen Dikken ◽

Nienke M. Moolenaar ◽

Marieke J. Schuurmans ◽

Niek J. de Wit ◽

...

Keyword(s):

Social Network ◽

Social Network Analysis ◽

Network Analysis ◽

Data Collection ◽

Older People ◽

Primary Healthcare ◽

Healthcare Professionals ◽

Interprofessional Collaboration ◽

Network Development ◽

Knowledge And Skills

Abstract Background Due to multimorbidity and geriatric problems, older people often require both psychosocial and medical care. Collaboration between medical and social professionals is a prerequisite to deliver high-quality care for community-living older people. Effective, safe, and person-centered care relies on skilled interprofessional collaboration and practice. Little is known about interprofessional education to increase interprofessional collaboration in practice (IPCP) in the context of community care for older people. This study examines the feasibility of the implementation of an IPCP program in three community districts and determines its potential to increase interprofessional collaboration between primary healthcare professionals caring for older people. Method A feasibility study was conducted to determine the acceptability and feasibility of data collection and analysis regarding interprofessional collaboration in network development. A questionnaire was used to measure the learning experience and the acquisition of knowledge and skills regarding the program. Network development was assessed by distributing a social network survey among professionals attending the program as well as professionals not attending the program at baseline and 5.5 months after. Network development was determined by calculating the number, reciprocity, value, and diversity of contacts between professionals using social network analysis. Results The IPCP program was found to be instructive and the knowledge and skills gained were applicable in practice. Social network analysis was feasible to conduct and revealed a spill-over effect regarding network development. Program participants, as well as non-program participants, had larger, more reciprocal, and more diverse interprofessional networks than they did before the program. Conclusions This study showed the feasibility of implementing an IPCP program in terms of acceptability, feasibility of data collection, and social network analysis to measure network development, and indicated potential to increase interprofessional collaboration between primary healthcare professionals. Both program participants and non-program participants developed a larger, more collaborative, and diverse interprofessional network.

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Mapping the Scientific Research on Healthcare Workers’ Occupational Health: A Bibliometric and Social Network Analysis

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17082625 ◽

2020 ◽

Vol 17 (8) ◽

pp. 2625 ◽

Cited By ~ 2

Author(s):

Bingke Zhu ◽

Hao Fan ◽

Bingbing Xie ◽

Ran Su ◽

Chaofeng Zhou ◽

...

Keyword(s):

Social Network ◽

Social Network Analysis ◽

Occupational Exposure ◽

Network Analysis ◽

Occupational Health ◽

Strength Training ◽

Healthcare Workers ◽

Health Workers ◽

Research Area ◽

Workplace Mental Health

In the last few years, the occupational health (OH) of healthcare workers (HCWs) has been shown increasing concern by both health departments and researchers. This study aims to provide academics with quantitative and qualitative analysis of healthcare workers’ occupational health (HCWs+OH) field in a joint way. Based on 402 papers published from 1992 to 2019, we adopted the approaches of bibliometric and social network analysis (SNA) to map and quantify publication years, research area distribution, international collaboration, keyword co-occurrence frequency, hierarchical clustering, highly cited articles and cluster timeline visualization. In view of the results, several hotspot clusters were identified, namely: physical injuries, workplace, mental health; occupational hazards and diseases, infectious factors; community health workers and occupational exposure. As for citations, we employed document co-citation analysis to detect trends and identify seven clusters, namely tuberculosis (TB), strength training, influenza, healthcare worker (HCW), occupational exposure, epidemiology and psychological. With the visualization of cluster timeline, we detected that the earliest research cluster was occupational exposure, then followed by epidemiology and psychological; however, TB, strength training and influenza appeared to gain more attention in recent years. These findings are presumed to offer researchers, public health practitioners a comprehensive understanding of HCWs+OH research.

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