Simulation modelling as a tool for knowledge mobilisation in health policy settings: a case study protocol

BACKGROUND

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.

METHODS/DESIGN

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.

DISCUSSION

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.

Further evidence of pleiotropy influencing speech and language: analysis of the DYX8 region

BACKGROUND/AIMS

Genetic studies have raised the possibility of common bases for cognitive linguistic disorders such as speech sound disorder (SSD), reading disorder (RD) and language impairment (LI). Thus, some of the same genes may jointly influence cognitive components within and between these three disorders. We examined the plausibility of this theory in a sample of families ascertained on the basis of a child with SSD.

METHODS

Using the method of generalized estimating equations to solve a bivariate family predictive model we obtained measures of comorbidity and familial aggregation of SSD and LI. We then used two methods of multipoint model-free linkage analysis to evaluate SSD and LI psychometric test measures over a region previously implicated in linkage studies of RD, DYX8 region, 1p34-p36.

RESULTS

Bivariate phenotypic analyses show evidence of comorbidity and within family aggregation and coaggregation of SSD and LI. In addition, two regions on chromosome 1 show suggestive evidence of linkage. The first region was previously reported in dyslexia studies. Our maximum linkage signal in this region measured articulation (p = 0.0009) in SSD sibling pairs. The second region is characterized by processes involved in language production, with the maximum linkage signal measuring listening comprehension (p = 0.0019) using all sibling pairs.

CONCLUSION

We conclude that the DYX8 region could bear genes controlling pleiotropic effects on SSD, LI and RD.

Speech production skills of nuclear family members of children with phonology disorders

The speech production skills of 38 school-aged siblings and 94 parents of children with phonology disorders were assessed by administering tasks involving the repetition of multisyllabic real and nonsense words, and "difficult-to-articulate" phrases and sentences. Results demonstrated that speech production, as measured by these tasks, continues to improve into adulthood. Furthermore, family members who reported histories of childhood speech and language problems performed more poorly on these challenging articulatory tasks than did individuals without such a history. These tasks were positively correlated with reading, spelling, and language achievement measures, thus suggesting a relationship between spoken and written language.

Subgrouping children with familial phonologic disorders

Familial aggregation of speech and language disorders was examined as a basis of subgrouping children with phonologic disorders. Fifty-nine children with phonologic disorders were subgrouped according to whether or not other nuclear family members reported a history of speech/language disorders. Thirty-four subjects (58%) reported at least one other nuclear family member affected and 25 subjects (42%) reported no other nuclear family members affected. Groups were compared on measures of articulation, phonology, language, and oral motor skills to determine if the familial phonologic subgroup presented a unique profile of speech and language deficits. Significant group differences were not observed. However, children with positive nuclear family histories tended to perform more poorly than children without histories on all tasks, although not reaching significance. Although all parents were considered to have achieved normal adult articulation, parents of children with positive family histories also tended to perform more poorly than parents of children with negative histories. Results suggested that poorer oral motor coordination and productive phonology may distinguish individuals with familial phonologic disorders from individuals with phonologic disorders of unknown origin.