ROOKScore leverages three primary data inputs, each capable of independent or collaborative utilization, to evaluate the well-being of your users. These inputs encompass user activity, sleep patterns, and overall readiness.
Data Inputs
Activity
Source data: Physical health summaries
Objective: Indicator of the percentage of daily activity achieved by the user
Basic required data: Age, gender, weight, height
Readiness
Source data: Sleep health summaries
Objective: Indicator of the user's cardiac well-being
Basic required data: Age, gender
Sleep
Source data: Sleep health summaries
Objective: Indicator of the quality of the user's sleep
Basic required data: Age
ROOK can generate several types of scores: in combination, individually, or in a hybrid form, utilizing some of the input options as we can read below.
Global Score: Derived by averaging scores from the three health score categories—activity, sleep, and readiness.
Activity-Readiness Score: Calculated by averaging scores from the activity and readiness sections, offering a comprehensive assessment of the user's physical activity and cardiac well-being.
Activity-Sleep Score: Computed by averaging scores from the activity and sleep sections, providing an overall evaluation of the user's physical activity and sleep quality.
Readiness-Sleep Score: Formulated by averaging scores from the readiness and sleep sections, delivering a comprehensive assessment of the user's cardiac well-being and sleep quality.
In the event that a wearable device fails to provide information for any of the required data inputs, ROOK will still generate a score, and the missing information will be flagged as null. This capability is rooted in the adaptability of the Global Score, which can work with information either individually or collectively, ensuring a comprehensive assessment even when specific data points are unavailable.
This flexibility arises from the option to configure the data inputs in your implementation, forming the basis for the ROOKScore for your clients. You can choose to use only one, two, or three inputs, and decide whether the weighting will be among two or three inputs or the remaining ones.
Therefore, the only consequence to consider is that if data is absent for a particular pillar, it will appear as null. As a client, you have the choice to weigh the score with the missing element, which may result in a lower score than expected.
For more details, please refer to our technical documentation.