Searchable Title

Development and Psychometric Testing of the Clinical Networks Engagement Tool. Copyright: Creative Commons License.

Reference Type

Journal Article

Authors, Section

Norris, J. M.; Hecker, K. G.; Rabatach, L.; Noseworthy, T. W.; White, D. E.

Title, Section

Development and Psychometric Testing of the Clinical Networks Engagement Tool. Copyright: Creative Commons License.

Publication Year

2017

Journal Title

PLoS One

Volume

12

Issue

3

Pages

e0174056

Availability

online

PMID

PMID: 28350834

DOI

10.1371/journal.pone.0174056

Abstract

Full Text Measurement tool is in S2 supplementary file on the webpage. BACKGROUND: Clinical networks are being used widely to facilitate large system transformation in healthcare, by engagement of stakeholders throughout the health system. However, there are no available instruments that measure engagement in these networks. METHODS: The study purpose was to develop and assess the measurement properties of a multiprofessional tool to measure engagement in clinical network initiatives. Based on components of the International Association of Public Participation Spectrum and expert panel review, we developed 40 items for testing. The draft instrument was distributed to 1,668 network stakeholders across different governance levels (leaders, members, support, frontline stakeholders) in 9 strategic clinical networks in Alberta (January to July 2014). With data from 424 completed surveys (25.4% response rate), descriptive statistics, exploratory and confirmatory factor analysis, Pearson correlations, linear regression, multivariate analysis, and Cronbach alpha were conducted to assess reliability and validity of the scores. RESULTS: Sixteen items were retained in the instrument. Exploratory factor analysis indicated a four-factor solution and accounted for 85.7% of the total variance in engagement with clinical network initiatives: global engagement, inform (provided with information), involve (worked together to address concerns), and empower (given final decision-making authority). All subscales demonstrated acceptable reliability (Cronbach alpha 0.87 to 0.99). Both the confirmatory factor analysis and regression analysis confirmed that inform, involve, and empower were all significant predictors of global engagement, with involve as the strongest predictor. Leaders had higher mean scores than frontline stakeholders, while members and support staff did not differ in mean scores. CONCLUSIONS: This study provided foundational evidence for the use of this tool for assessing engagement in clinical networks. Further work is necessary to evaluate engagement in broader network functions and activities; to assess barriers and facilitators of engagement; and, to elucidate how the maturity of networks and other factors influence engagement.

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