Beta2 plan”

We are trying to bring most of the information we are learning from mindgrapher into a single, simple report for the clinician. These figures will be accompanied by a simple verbal description

I will call this the homepage report. this will be the summary

libraries and data

Variable MAP

this creates a map of questions, short variable names, and sentiment (positive versus negative)

This illustrates one way to work with the data frame.This is the RDS file from mindgrapher

There is no subject ID. nore is the question id unique

I have created a map of items and the short “description” for use in graphing

As we add items, we will need to expand this map

I have also labeled each item as positive or negative, which can be used in the lollipop

## # A tibble: 42 × 3
##    Question                                                Description Dimension
##    <chr>                                                   <chr>       <chr>    
##  1 I was able to change my behavior, when changing helped… PAbletoCha… Positive 
##  2 I did things that hurt my connection with people who a… PHurtConne… Negative 
##  3 I was able to experience a range of emotions appropria… PExpRangeo… Positive 
##  4 I struggled to keep doing something that was good for … PStruggled… Negative 
##  5 I didn't find a meaningful way to challenge myself.     PNoMeaning… Negative 
##  6 I acted in ways that helped my physical health.         PHelpedHea… Positive 
##  7 My thinking got in the way of things that were importa… PThinkingG… Negative 
##  8 I paid attention to important things in my daily life.  PAttendedt… Positive 
##  9 I did things only because I was complying with what ot… PComplied   Negative 
## 10 I stuck to strategies that seemed to have worked.       PStucktoWo… Positive 
## # ℹ 32 more rows

Routine Outcome Monitoring–are there trends in the data (particularly in well-being outcomes)

Because the example mindgrapher data frame is a bit to sparse to be of use, i will provide a sample data set

Most systems include routine outcome monitoring to track progress over time. These figures can be enhanced by integrating tests for improvement, identifying trends, and flagging instances where meaningful change is not occurring. Such additions provide actionable insights, helping to identify areas requiring intervention and ensuring that progress remains on track.

We may be able to use a previous figure on this home page report, problably the one that detects changes.

the user should be able to select any item and see it ploted in the report page

I arimax looping through every variable for every DV for one person

This is used as example, but you can get the data from iARIMAX results already generated in mindgrapher.You can get significance from i arimax or machine learng. the original implementation is faster.

RIF Lollipop Plot

Reliable

• Represented by a blue circle.
• Indicates statistical significance in analyses such as ARIMAX or machine learning models.
• Orange indicates not reliable

Important

• Reflected by the strength of the relationship or distance from zero on the graph.
• Derived from ARIMAX or decision tree estimates.

Feasible to Change

• Depicted by the size of the circle:
  • Positive Behavior (infrequent): Assumed there is room to improve.
• Negative Behavior (frequent): Presumed there is room to diminish.
• Circle size maps to the frequency of the behavior. Varies from 0 to 100
• Alternatively, feasibility could be based on inputs from a clinician.