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Table 2 Characteristics of included studies

From: How the study of networks informs knowledge translation and implementation: a scoping review

Citation

Study purpose

Type of network/setting

Network size (# participants)

Data collection methods

Theoretical perspective

Zappa 2011 [29]

To describe relationships for knowledge sharing about a new drug

Physician network within a group of 338 hospitals

784 physicians

Survey

Diffusion of innovation

Yousefi-Nooraie 2014 [37] (same study as 29)

To assess factors associated with information seeking in public health

Information seeking, expertise recognition, and friendship networks within an urban public health department

15 managers and 13 professional consultants (n = 28)

Survey

Transactive memory theory; social exchange theory

Yousefi-Nooraie 2012 [36] (same study as 30)

To identify the structure of intra-organizational knowledge flow for evidence informed practice

Information sharing network

170 directors, managers, supervisors, consultants, epidemiologists, practitioners, and administrative support

Social influence theory

Tasselli 2015 [22]

To describe knowledge transfer between professions, effectiveness of central actors and brokers, and the influence of organizational hierarchy on access to knowledge

Knowledge transfer network in a hospital department

n = 118

53 physicians and 65 nurses

Survey and interviews

Sociology of professions theory; SNA paradigm

Sibbald 2013 [21]

To explore patterns of information exchange among colleagues in inter-professional teams

Information seeking and sharing networks within six interdisciplinary primary health care teams

n = 28 (nurses, physicians, residents, allied health professionals, e.g., nurses, dietician, social worker); two sites: n1 = 19 and n2 = 8.

Survey and semi-structured interviews

SNA paradigm

Racko 2018 [47]

To examine the influence of social position on knowledge exchange over time

Knowledge exchange networks within three academic-clinical KT programs

three surveys: n1 = 66; n2 = 70; n3 = 42 clinicians and academics

Surveys

Social capital theory

Quinlan 2013 [42]

To explore mechanisms of information sharing across professional boundaries

Knowledge contribution to decision-making by members within multidisciplinary primary healthcare teams (two clinical decisions, so two networks for each of four clinical teams)

Nurse practitioners (n = 13 or fewer)

Online survey

Habermas’ theory of communicative power

Paul 2015 [35] (portion of data from study [45])

To test a model examining the role of triadic dependence on reciprocity and homophily

Influence network

33 physicians

Surveys

SNA paradigm

Patient care network

135 physicians

Menchik 2017 [44]

To explore the type of knowledge valued by physicians and the influence of hospital prestige on evidence-seeking behavior and perceived esteem by peers

Information seeking and clinical case discussion networks, within six hospitals

126 physicians

Survey

Social influence theory

Mascia 2018 [27]

To explore theoretical mechanisms explaining network formation across clinical sectors

Advice-seeking networks within two regional health authorities

97 pediatricians

Survey

Balance theory; structural holes perspective; homophily principle

Mascia 2014 [33]

To explore the association between connectedness with colleagues and frequency of evidence use within a physician network

Collaboration networks within 5 health authorities

104 pediatricians

Survey

Diffusion of innovation; social influence theory; social contagion; strength of weak ties [82]

Mascia 2015 [48] (same data as study [30, 32])

To explore the influence of homophily on tie formation

    

Mascia 2011a [30] (same data as study [32, 48]

To determine the association between attitudes toward EIP and network structure and to identify predictors of collaborative ties

EIP advice-sharing networks within 6 hospitals

297 physicians

Survey

Homophily principle

Mascia 2013 [32] (same data as study [30, 48])

To explore the relationship between attitudes toward EIP and network position

   

Core/periphery model; structural holes

Mascia 2011b [31] (same study as [30, 32, 48])

To explore the association between network structure and propensity to adopt EIP

 

207 physicians

 

Social contagion; structural holes perspective

Long 2014 [41]

(same data as study [40])

To examine the influence of clustering on past, present, and future collaborations within a translational research network

Past, present, and intended collaboration networks within a research network

68 researchers and clinicians

Online survey

SNA paradigm

Long 2013 [40] (same data as study [41])

To identify key players within a research network, their common attributes, and their perceived influence, power, and connectedness

Research collaboration and dissemination networks within a research network

Keating 2007 [45]

To describe the network of influential discussions among physicians and to predict network position

Frequency of influential conversations relevant to practice within primary care

38 physicians

Survey

SNA paradigm

Heijmans 2017 [26]

To explore relationships between network properties and quality of care

Information exchange networks within 31 general practices

180 health professionals (physicians, residents, nurses, pharmacy assistants, social workers)

Survey document review (i.e., intervention and referral charting)

SNA paradigm

Guldbrandsson 2012 [38]

To identify potential national opinion leaders in child health promotion

Discussion network within national child health promotion context

153 researchers, public health officials, pediatricians and other individuals

Emailed survey item

Diffusion of innovation

Friedkin 2010 [25]

To examine the association between discussion networks, marketing, and physician prescribing practices

Advice and discussion networks of physicians (re-analysis of Coleman, Katz and Menzel, 1966 historical data on medication adoption)

125 physicians

Document review (i.e., prescription records of pharmacies)

Diffusion of innovation; social contagion; cohesion; structural equivalence

Burt 1987 [24]

To test social contagion theory by examining cohesion versus structural equivalence as drivers of tie formation

Doumit 2014 [34]

To identify opinion leaders and their impact on EIP

Advice networks of craniofacial surgeons within 14 countries

59 craniofacial surgeons

Online survey

Diffusion of innovation

Di Vincenzo 2017 [28]

To explain the impact of research productivity on tie redundancy (i.e., connections that lead to the same people/information)

Advice seeking networks within and external to a health authority containing 6 hospitals

228 physicians

Survey

Structural holes perspective; homophily perspective

Bunger 2016 [43]

To evaluate change in advice ego-network composition and its impact on whole network structure following implementation of a “learning collaborative” model in improve care quality

Advice networks of clinicians (psychologists, social workers, others) and leadership in 32 behavioral health agencies

132 clinicians, supervisors and senior leaders

Surveys

SNA paradigm

Ankem 2003 [23]

To understand communication flow and its influence on awareness/adoption of a treatment, and to identify opinion leaders with influence

Frequent discussion networks within a sample drawn from an online physician directory

32 interventional radiologists

Phone interviews

Diffusion of innovation; SNA paradigm

D’Andreta 2013 [39]

To compare the network structures of three research/KT program initiatives

Informal advice giving and seeking networks within each of three academic-clinical KT programs

n = ~ 260 (directors, managers, program leaders, knowledge brokers, researchers, and others unspecified)

Online survey

SNA paradigm; Epistemic differences perspective

  1. SNA social network analysis, EIP evidence informed practice, KT knowledge translation. Where indicated by the articles’ authors, the dependent variable is designated using bold text