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. 2019 Jul;102(7):1389-1396.
doi: 10.1016/j.pec.2019.02.026. Epub 2019 Mar 2.

Development of a measure of collective efficacy within personal networks: A complement to self-efficacy in self-management support?

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Development of a measure of collective efficacy within personal networks: A complement to self-efficacy in self-management support?

Rebecca Band et al. Patient Educ Couns. 2019 Jul.
Free article

Abstract

Objective: To develop and evaluate the Collective Efficacy of Networks (CENS) questionnaire to measure perceived collective efficacy within personal social networks.

Methods: A mixed methods approach was used, guided by theory and with extensive input from adults with long-term conditions who completed the initial questionnaire (n = 78) with test-retest assessed at 2 weeks (n = 68). A second sample (n = 85) completed a postal questionnaire including CENS, theoretically linked constructs (self-efficacy, social support) and health outcomes (loneliness, mental and physical health).

Results: Principal components analysis demonstrated a two-factor structure with 12-items selected to represent Network responsiveness (8 items, Cronbach's alpha = 0.896) and Access to collective efficacy (4 items, Cronbach's alpha = .773). Good test-retest reliability was established for both subscales (ricc = .793-.853). Network responsiveness was associated with self-efficacy (r = 342, p = . < 001) and social support (r = .407, p < .001) and predicted reduced loneliness. Access to collective efficacy significantly predicted better mental health; the predictive validity of the subscales improved when combined with self-efficacy.

Conclusion: The CENS is an acceptable and psychometrically robust measure of collective efficacy in personal social networks.

Practice implications: Measuring collective efficacy with self-efficacy will provide useful information for researchers and policymakers interested in capacity for self-management and social determinants of behaviour change.

Keywords: Assessment; Collective efficacy; Personal communities; Psychometric evaluation; Social networks.

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