Are Public Health Workers Aware of What They Don't Know?

Kerby, Dave S.; Brand, Michael; Elledge, Brenda L.; Johnson, David L.; Magas, Olga K.

doi:10.1089/bsp.2005.3.31

Cited by 15 publications

(6 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…5 The post-9/11 literature is replete with information regarding preparedness and the pivotal role played by the public health workforce. [6][7][8][9][10][11][12][13][14] Likewise, experienced public health practitioners have offered their thoughtful approaches for overall public health agency preparedness, particularly in conjunction with critical system partners. [15][16][17][18][19][20][21] In addition, innovative assessment tools have been developed to assist state and local health departments in determining the community's overall level of readiness.…”

mentioning

confidence: 99%

A State-Based Analysis of Public Health Preparedness Programs in the United States

et al. 2006

View full text Add to dashboard Cite

show abstract

mentioning

confidence: 99%

A State-Based Analysis of Public Health Preparedness Programs in the United States

et al. 2006

View full text Add to dashboard Cite

show abstract

“…The handoff 4 has had the lowest mean score of satisfaction. It meets the assumption of Kerby et al (2005): a system with adequate resources does not ensure, by itself, a properly functioning system, without certain threshold of connectivity. Note that, in Figure 2, most of the relationships among the actors are asymmetric; the actors are Correlations among actor information centrality (AIC) and others centrality measures (p = 0,000) Centrality measure AIC/Handoff 1 AIC/Handoff 2 AIC/Handoff 3 AIC/Handoff 4 AIC/Handoff 5 AIC/Handoff 6 AIC/Handoff 7 Degree 0,93 0,94 0,94 0,87 0,93 0,95 0,98 Closeness 0,93 1,00 0,97 0,88 0,98 0,91 0,93 Betweenness 0,60* 0,94 0,87 0,65** 0,76** 0,77** 0,76** Eigenvector 0,98 1,00 0,70* 0,95 0,99 0,91 0,99 * p = 0,02 ** p = 0,01 positioned more on the periphery of the network and express low connectivity.…”

Section: Discussionmentioning

confidence: 99%

“…This concept is useful to describe the integration and coordination of activities in public health, among other areas. Even if a system has adequate resources in terms of technology, training and funding, such components do not ensure alone a properly functioning system, without certain threshold of connectivity (Kerby et al, 2005).…”

Section: Centrality Measures In Social Networking Analysismentioning

confidence: 99%

The nurse as an integration agent in handoff: A social networks analysis perspective

Silva¹,

Avelar²,

Farina³

2014

Afr. J. Bus. Manage.

View full text Add to dashboard Cite

The growing interest in social networks, in health services, follows international pressure by improving quality and reducing costs in this sector. Identifying the most important actors in a social network is one of the applications of graph theory in social network analysis (SNA). Socialization among health professionals (actors) and their structural positions, in social networks, are important factors to be considered in developing strategies, which include information dissemination and influence. This research applied SNA to identify the actors with the greatest influence during handoff in a hospital. Data were collected in the second half of 2012, in the city of São Paulo. Semi-structured interviews have been conducted with actors in six handoffs. A seventh handoff has been created, as ideal hypothetical model, to compare the distinguishing features among the handoffs. The nurse in the unit of origin emerges as the actor with greater popularity (degree, eigenvector), greater influence or control (betweenness) and better access to information on the handoff (closeness, actor information centrality). A nurse is, possibly, an important categorical role to facilitate actions of integration during a handoff.

show abstract

“…"[3] The concept has been described as useful for describing the integration and coordination of the public health and emergency management network[3]. It has been reported that even if a system has ample resources in terms of equipment, training, and funding, these components will not function optimally if the system does not reach a threshold level of connectivity[4]. If, however, organizations have developed strong and mutual relationships, research suggests that the system as a whole will likely manage the crisis more efficiently and have greater capacity to adapt and improvise should an unexpected event outside of the specific action and contingency plans occur[3,4].…”

Section: Introductionmentioning

confidence: 99%

Assessing the congruence between perceived connectivity and network centrality measures specific to pandemic influenza preparedness in Alberta

2010

View full text Add to dashboard Cite

BackgroundRecent research has suggested that perceived organizational connectivity may serve as an important measure of public health preparedness. Presumably, organizations with higher perceived connectivity also have a greater number of actual organizational ties. Using network analysis, we evaluate this presumption by assessing the correlation between perceived organizational connectivity and reported inter-organizational connections.MethodsDuring late 2007-early 2008, representatives from organizations involved in the delivery of public health systems in Alberta were asked to complete an online questionnaire on public health preparedness. Organizational jurisdictional information was collected. Items from Dorn and colleagues connectivity scale (2007) were used to measure perceived organizational connectivity. Inter-organizational network data on formal connections in the area of pandemic influenza preparedness were collected using a roster approach. These data were imported into UCINET to calculate in- and out-degree centrality scores for each organization. One-way ANOVA tests assessed if perceived connectivity and in- and out-degree centrality varied among jurisdictions. Pearson correlation coefficients were used to assess the correlation of perceived connectivity and in- and out-degree centrality.ResultsSignificant mean differences among jurisdictions were observed for in-degree (F(3,116) = 26.60, p < 0.001) and between provincial and lower jurisdictions for out-degree centrality (F(3,116) = 5.24, p < 0.01). Higher jurisdictions had higher average centrality. Perceived organizational connectivity was correlated with out-degree (r(123) = 0.22, p < 0.05) but not in-degree centrality (r(123) = -0.07, p > 0.05).ConclusionsThe results suggest in terms of pandemic preparedness that perceived connectivity may serve as a partial proxy measure of formal out-degree network connectivity.

show abstract

Are Public Health Workers Aware of What They Don't Know?

Cited by 15 publications

References 30 publications

A State-Based Analysis of Public Health Preparedness Programs in the United States

A State-Based Analysis of Public Health Preparedness Programs in the United States

The nurse as an integration agent in handoff: A social networks analysis perspective

Assessing the congruence between perceived connectivity and network centrality measures specific to pandemic influenza preparedness in Alberta

Contact Info

Product

Resources

About