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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Simulation modelling as a tool for knowledge mobilisation in health policy settings: a case study protocol
|
|---|---|
| Published in |
Health Research Policy and Systems, September 2016
|
| DOI | 10.1186/s12961-016-0143-y |
| Pubmed ID | |
| Authors |
L. Freebairn, J. Atkinson, P. Kelly, G. McDonnell, L. Rychetnik |
| Abstract |
Evidence-informed decision-making is essential to ensure that health programs and services are effective and offer value for money; however, barriers to the use of evidence persist. Emerging systems science approaches and advances in technology are providing new methods and tools to facilitate evidence-based decision-making. Simulation modelling offers a unique tool for synthesising and leveraging existing evidence, data and expert local knowledge to examine, in a robust, low risk and low cost way, the likely impact of alternative policy and service provision scenarios. This case study will evaluate participatory simulation modelling to inform the prevention and management of gestational diabetes mellitus (GDM). The risks associated with GDM are well recognised; however, debate remains regarding diagnostic thresholds and whether screening and treatment to reduce maternal glucose levels reduce the associated risks. A diagnosis of GDM may provide a leverage point for multidisciplinary lifestyle modification interventions. This research will apply and evaluate a simulation modelling approach to understand the complex interrelation of factors that drive GDM rates, test options for screening and interventions, and optimise the use of evidence to inform policy and program decision-making. The study design will use mixed methods to achieve the objectives. Policy, clinical practice and research experts will work collaboratively to develop, test and validate a simulation model of GDM in the Australian Capital Territory (ACT). The model will be applied to support evidence-informed policy dialogues with diverse stakeholders for the management of GDM in the ACT. Qualitative methods will be used to evaluate simulation modelling as an evidence synthesis tool to support evidence-based decision-making. Interviews and analysis of workshop recordings will focus on the participants' engagement in the modelling process; perceived value of the participatory process, perceived commitment, influence and confidence of stakeholders in implementing policy and program decisions identified in the modelling process; and the impact of the process in terms of policy and program change. The study will generate empirical evidence on the feasibility and potential value of simulation modelling to support knowledge mobilisation and consensus building in health settings. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Curaçao | 1 | 25% |
| United States | 1 | 25% |
| Unknown | 2 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Scientists | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 156 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | <1% |
| Unknown | 155 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 25 | 16% |
| Researcher | 25 | 16% |
| Student > Master | 17 | 11% |
| Student > Doctoral Student | 12 | 8% |
| Student > Bachelor | 9 | 6% |
| Other | 28 | 18% |
| Unknown | 40 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 26 | 17% |
| Nursing and Health Professions | 24 | 15% |
| Social Sciences | 16 | 10% |
| Business, Management and Accounting | 8 | 5% |
| Computer Science | 6 | 4% |
| Other | 30 | 19% |
| Unknown | 46 | 29% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 October 2016.
All research outputs
#13,244,405
of 22,889,074 outputs
Outputs from Health Research Policy and Systems
#942
of 1,216 outputs
Outputs of similar age
#164,969
of 320,659 outputs
Outputs of similar age from Health Research Policy and Systems
#13
of 20 outputs
Altmetric has tracked 22,889,074 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,216 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.1. This one is in the 20th percentile – i.e., 20% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 320,659 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 20 others from the same source and published within six weeks on either side of this one. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.