Priority 5: Extend the scope of the readyforwhatsnext model

Why?

We hope that once launched, the readyforwhatsnext MVP systems model will be transparent, reusable and updatable and usful for addressing some important topics in youth mental health. However, there will inevitably be a much greater number of topics for which that the MVP model lacks the scope to adequately address. The two main scope limitations of the MVP model are expected to be omissions and level of abstraction. Some relevant system features will be ommitted from representation by the MVP model - for example our pipeline of platforms modules does not currently include any planned modules for modelling the operations of digital mental health services or schools. System features that are represented in the MVP model may only have one level of abstraction, which may be either too simple or too complex to be appropriately applied to some modelling goals.

What?

We plan to progressively extend the scope of readyforwhatsnext and the range of decision topics to which it can validly be applied. The most important initial types of help we need to achieve this goal are funding, projects and advice.

How?

The two main strategies for extending readyforwhatsnext are to translate existing models and develop new models. The process for developing new models is outlined elsewhere as the steps required to undertake a modelling project.

Translating existing models involves the following steps:

1. Identify existing computational model(s) of relevant youth mental health systems to be redeveloped using the ready4 framework. Processes for identifying models could include:

• A modelling team reviewing some of the models that they have previously implemented using other software; and/or

• A systematic search of published literature and/or model repositories.

2. (Optional - only if a single project plans to redevelop multiple models) Develop a data extraction tool into which data on relevant model features will be collated and categorised.

3. Extract data on relevant model features. In the (highly likely) event that the reporting and documentation of the model being redeveloped lacks important details:

• Contact the original model authors for assistance; and/or

• Seek relevant advice to help determine plausible / appropriate values for missing data.

3. Author module libraries for representing the included model(s).

4. Author labelled open access datasets of model input data (which can be set to private for now).

5. Author analysis and reporting programs designed to replicate the original modelling study / studies.

6. Compare results from original and replication analyses. Ascertain the most plausible explanations for any divergence between results. Where this explanation relates to an error or limitation in the new readyforwhatsnext modules or analysis programs that have been authored, fix these issues.

7. Complete documentation of model libraries, datasets and analyses.

8. (If not already done) Publish / link to datasets on the ready4 Dataverse and share releases of libraries and programs in the ready4 Zenodo community.

When?

As our current focus in on developing the MVP model, we are not yet actively pursuing this priority. That will change if we are successful in securing more support from funders. In the mean time, if you are a researcher and/or modeller who is interested in leading a project that can help extend readyforwhatsnext, you can contact our project lead for guidance and/or to discuss the potential for collaborations.