scholarly journals Basic Criteria, Models, and Indicators of Intersectoral Collaboration in Health Promotion: A Scoping Review

2021 ◽  
Author(s):  
Mohammad Reza Amir Esmaili ◽  
Behzad Damari ◽  
Ahmad Hajebi ◽  
Noora Rafiee ◽  
Reza Goudarzi ◽  
...  
Keyword(s):  
Health Promotion ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Scoping Review ◽  
Web Of Science ◽  
Decision Makers ◽  
Macro Level ◽  
Intersectoral Collaboration ◽  
Micro Level

Background: In this study, the basic criteria, models, and indicators of intersectoral collaboration in health promotion were investigated to facilitate the implementation of collaboration. Methods: This scoping review was conducted using datasets of Embase, Web of Science, Scopus, and PubMed, and search engines of Google, Google Scholar, and ProQuest. Results: 52 studies were included, and 32 codes in Micro, Meso, and Macro level, were obtained. Micro-level criteria had the highest frequency. Among the models used in the reviewed studies, social network analysis, Diagnosis of Sustainable Collaboration, Bergen, and logic models had the highest frequency. Among the indicators studied, the number of participants and the level of collaboration as well as its sustainability were the most frequent indicators. Conclusion: The findings identified the most important and widely used criteria, models, and indicators of intersectoral collaboration in health promotion which can be useful for decision-makers and planners in the domain of health promotion, in designing, implementing, and evaluating collaborative programs.

A stakeholder analysis of community-led collaboration to reduce health inequity in a deprived neighbourhood in South Korea

2018 ◽  
Vol 27 (2) ◽  
pp. 35-44
Author(s):  
Hyun-Hee Heo ◽  
Woojin Jeong ◽  
Xian Hua Che ◽  
Haejoo Chung
Keyword(s):  
Health Promotion ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Service Providers ◽  
Stakeholder Analysis ◽  
Current Status ◽  
Intersectoral Collaboration ◽  
Deprived Neighborhoods ◽  
Health Promotion Interventions

Intersectoral collaboration amongst health and other sectors, as well as between government and non-governmental organisations, has been highlighted as a way to improve health equity. We used a mixed-methods approach to assess collaborative relationships between multiple government sectors and civil society and to suggest possible health promotion interventions and policy alternatives for the urban poor in deprived neighborhoods. A total of 18 participants involved in health promotion interventions and policy processes related to the inner-city area of Seoul were recruited using purposive sampling methods. Participants included stakeholders working for or engaging in governments (3), public health care institutions (5), social service providers (3), community-based organisations (CBOs) (4) and faith-based organisations (3). We conducted semi-structured, one-on-one interviews and then collected survey data. Quantitative data were analysed using social network analysis, and qualitative data were analysed through iterative and consensus processes. The social network analysis indicated that a CBO plays the most substantial role in sharing and controlling informational resources to promote health. A stakeholder analysis showed that the CBO neutrally and negatively viewed the possibility of collaboration with other stakeholders. Three themes related to challenges to intersectoral collaboration emerged: (1) lack of trust and communication, (2) need of a coalition with a committed leading actor for future collaboration and (3) organisational and political silos within and across public sectors. Increased understanding of the current status of and challenges to collaboration can inform the planning and implementation of complex intervening strategies and policies tailored to vulnerable people in deprived neighborhoods. Community-led collaborative actions empower people in marginalised communities to envision a healthier community.

scholarly journals Using social network analysis to plan, promote and monitor intersectoral collaboration for health in rural India

PLoS ONE ◽  
2019 ◽  
Vol 14 (7) ◽  
pp. e0219786
Author(s):  
Connie Hoe ◽  
Binita Adhikari ◽  
Douglas Glandon ◽  
Arindam Das ◽  
Navpreet Kaur ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Rural India ◽  
Intersectoral Collaboration

scholarly journals Social Network Analysis in Healthcare Settings: A Systematic Scoping Review

PLoS ONE ◽  
2012 ◽  
Vol 7 (8) ◽  
pp. e41911 ◽  
Author(s):  
Duncan Chambers ◽  
Paul Wilson ◽  
Carl Thompson ◽  
Melissa Harden
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Scoping Review ◽  
Healthcare Settings

scholarly journals A scoping review on the current and potential use of social network analysis for evaluation purposes

Evaluation ◽  
2018 ◽  
Vol 24 (3) ◽  
pp. 325-352 ◽  
Author(s):  
Lisa Popelier
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Scoping Review ◽  
Social Science Research ◽  
Science Research ◽  
Network Structures ◽  
Alternative Sources ◽  
Informal Relations ◽  
Potential Use

The pervasiveness and importance of relationships and networks has fueled the development of the social network analysis approach, which considers structural relationships to be primary causes of societal outcomes. While the potential of social network analysis has been demonstrated and discussed extensively in social science research, relatively little is known about the current and potential use of social network analysis for evaluation purposes. This scoping review of journal articles reveals that evaluators use social network analysis because of its ability to identify key stakeholders, assess network structures and relationships quantitatively, reveal informal relations and visualize even complex networks. However, challenges arise when interpreting findings, determining causation between network structures and outcomes and disseminating evaluation results in an ethically responsible manner. The review concludes that the evaluation field―especially in the development sector―would benefit greatly from increased use of social network analysis, but that this would first require improved use of alternative sources of network data, qualitative methods and inferential statistics that will enable evaluators to move beyond descriptive network analysis.

Relationships between public health faculty and decision makers at four governmental levels: a social network analysis

2018 ◽  
Vol 14 (3) ◽  
pp. 499-522 ◽  
Author(s):  
Nasreen S Jessani ◽  
Carly Babcock ◽  
Sameer Siddiqi ◽  
Melissa Davey-Rothwell ◽  
Shirley Ho ◽  
...  
Keyword(s):  
Public Health ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Decision Makers

scholarly journals Value of social network analysis for developing and evaluating complex healthcare interventions: a scoping review

BMJ Open ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. e039681
Author(s):  
Linda C Smit ◽  
Jeroen Dikken ◽  
Marieke J Schuurmans ◽  
Niek J de Wit ◽  
Nienke Bleijenberg
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Complex Intervention ◽  
Scoping Review ◽  
Complex Interventions ◽  
Intervention Research ◽  
Healthcare Intervention ◽  
Scoping Reviews ◽  
Healthcare Interventions

ObjectivesMost complex healthcare interventions target a network of healthcare professionals. Social network analysis (SNA) is a powerful technique to study how social relationships within a network are established and evolve. We identified in which phases of complex healthcare intervention research SNA is used and the value of SNA for developing and evaluating complex healthcare interventions.MethodsA scoping review was conducted using the Arksey and O’Malley methodological framework. We included complex healthcare intervention studies using SNA to identify the study characteristics, level of complexity of the healthcare interventions, reported strengths and limitations, and reported implications of SNA. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews 2018 was used to guide the reporting.ResultsAmong 2466 identified studies, 40 studies were selected for analysis. At first, the results showed that SNA seems underused in evaluating complex intervention research. Second, SNA was not used in the development phase of the included studies. Third, the reported implications in the evaluation and implementation phase reflect the value of SNA in addressing the implementation and population complexity. Fourth, pathway complexity and contextual complexity of the included interventions were unclear or unable to access. Fifth, the use of a mixed methods approach was reported as a strength, as the combination and integration of a quantitative and qualitative method clearly establishes the results.ConclusionSNA is a widely applicable method that can be used in different phases of complex intervention research. SNA can be of value to disentangle and address the level of complexity of complex healthcare interventions. Furthermore, the routine use of SNA within a mixed method approach could yield actionable insights that would be useful in the transactional context of complex interventions.

scholarly journals SECRET KILLERS “AFTER WIKILEAKS”: MAPPING, EVOLUTIONS, AND TAXONOMY OF RADICAL LEAKING

2020 ◽  
Author(s):  
Luke Heemsbergen
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Systematic Study ◽  
Democratic Theory ◽  
Ideal Type ◽  
Macro Level ◽  
Practice Analysis ◽  
Technical Practice ◽  
Material Practice

This paper is concerned with mapping the socio-material ecosystems of online leaks projects that followed WikiLeaks. The period of initial popularisation/infamy of WikiLeaks (2006-2015) correlates with an emergence of over 90 less-known radical online disclosure projects designed to ""Kill Secrets"" (Greenberg 2012). We offer the first systematic study of the decentralised and widely disparate ecosystem of leaks projects to build a taxonomy of leaks sites (n:94) from various observable socio-technical vectors. Affordances tied to user and technical practice, vectors such as self-identified thematic focus (issue, region, etc.), and measures of publication efficacy for each site are all open coded to discern patterns and clusters of practice. Analysis then shifts to mapping of visible interrelationships between sites via social network analysis (SNA) for further insight to the ecology of leaks sites. Taxonomy over typology signals observing material practice without predetermined ideal type, and normative links to agonistic democratic theory. At a macro level our findings suggest, an ecology of leaks sites blossomed and died, with only a handful of sites remaining online, or having ever actually functioned. Micro to Meso analysis of practices show how leaks sites' socio-technical materiality helps shape both efficacy and normative goals, from which unique and sometimes agonistic normative governmental functions can be inferred. Discussion of findings then critically assess how digital leaks served (and severed) ties to already problematic equations of 'transparency' and democracy from a frame of agonistic and algorithmic government practices (Heemsbergen, 2016; Ananny and Crawford, 2016) and suggest tentative paths forward.

scholarly journals Who Is the Keyman? Integrating Two-Stage DEA and Social Network Analysis to Evaluate Operational and Environmental Efficiency in the Semiconductor Industry

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Tzu-Yi Fang
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Semiconductor Industry ◽  
Operational Efficiency ◽  
Environmental Efficiency ◽  
Decision Makers ◽  
Network Graph ◽  
Two Stage ◽  
A Company

The study considers the semiconductor industry’s business process to be made up of two stages. In the business development process, a company generates profit and consumes energy while polluting the environment. After the two-stage data envelopment analysis approach was employed for calculating the operational efficiency and environmental efficiency, social network analysis was used to compare the manner in which the internal advantages or individual process factors of 28 semiconductor companies contribute to efficiency. A network graph was plotted to visualize relationships, with each node in the network graph representing a company. This graph was plotted to help decision-makers and manufacturers understand information communication among companies and the importance of the company in the network and help companies develop a mutual understanding to improve operational efficiency. The results of the study indicated that having an efficient company does not necessarily mean that the company plays a key role in the entire industry. The results provide decision-makers with references for improvements and information for learning from these references.

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