Exploring Community Collaborations: Social Network Analysis as a Reflective Tool for Public Health

Kothari, Anita; Hamel, Nadia; MacDonald, Jo-Anne; Meyer, Mechthild; Cohen, Benita; Bonnenfant, Dorothy

doi:10.1007/s11213-012-9271-7

Cited by 40 publications

(35 citation statements)

References 36 publications

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“…SNA provides a way to identify the structure of a network, providing insight into the influence of the network structure on individuals within a group. What is important for IKT is that SNA findings can be transformed into sociograms, or easy-to-understand visual depictions of relationships that have been used for important discussions about research findings with knowledge users 27 28…”

Section: Discussionmentioning

confidence: 99%

Integrated knowledge translation: digging deeper, moving forward

Kothari

Wathen

2017

J Epidemiol Community Health

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Section: Discussionmentioning

confidence: 99%

Integrated knowledge translation: digging deeper, moving forward

Kothari

Wathen

2017

J Epidemiol Community Health

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“…Assessment of the applied models revealed that there was a fairly good variation in studies. The applied models were: DISC (17)(18)(19)(20), Bergen (11,14), Himelman (15), network analysis (16), social network analysis (10,21), act for life collaboration continuum (22), Tukman (23), collective impact approach (24), system analysis (25), and logic (26,27).…”

Section: Results Of the Extraction Of Criteria Models And Indicatorsmentioning

confidence: 99%

Basic Criteria, Models, and Indicators of Intersectoral Collaboration in Health Promotion: A Scoping Study

Rafiee

Damari

Hajebi

et al. 2020

Preprint

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Background: The healthcare sector has a small share in community health, and other sectors are actively involved in this domain. Therefore, only by a collective and collaborative action can health promotion interventions be properly implemented. In order to have intersectoral collaboration in the domain of healthcare, basic criteria are required as an operational guide for the successful implementation of such collaborations. A specific framework is also required so that the programs can be properly implemented accordingly. After the implementation, the success or failure of the collaborative action will be determined by assessing the effectiveness of the actions taken using an appropriate assessment system (e.g., indicators). 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. Original articles, review articles, and reports were included in this study. In terms of subject, articles which referred to the basic criteria, models, or indicators of intersectoral collaboration in health promotion were included. Results: A total of 52 studies were included in the final analysis, and 32 codes in three categories (micro, meso, and macro) were obtained. Micro-level intersectoral collaboration criteria had the highest frequency. Among the models used in the reviewed studies, social network analysis (SNA), Diagnosis of Sustainable Collaboration (DISC), Bergen, and logic models had the highest frequency in health promotion. 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.

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“…Second, clinic leaders and policymakers could use these results to strategically develop a stronger network through resource and capacity building . For example, the identification of the isolated clinics and referral sites represents an opportunity for engagement and to build a stronger connection with those sites.…”

Section: Discussionmentioning

confidence: 99%

“…For example, network analysis has been used to identify prominent leaders in a network and how organizations within a network work together to address specific public health concerns such as HIV/AIDS, tobacco control, or cancer support . Network analysis has also been used to inform interventions that strengthen an existing health network . The use of network analysis to specifically study rural health care, however, is limited.…”

mentioning

confidence: 99%