Skip to main content

Automated Interventions

mindLAMP supports automated interventions that respond to participant data in real time. These can be rule-based (triggered by specific conditions) or adaptive (adjusting based on patterns).

Types of Interventions​

Rule-Based Interventions​

Trigger actions when specific conditions are met. For example:

  • Send a notification when a participant's mood score drops below a threshold.
  • Deliver a breathing exercise when stress indicators are elevated.
  • Alert the care team when a participant has not completed activities for several days.

Adaptive Interventions​

Adjust intervention parameters based on accumulated data. For example:

  • Modify survey frequency based on symptom severity.
  • Personalize content recommendations based on engagement patterns.
  • Escalate care team notifications based on trend analysis.

Implementation​

Interventions are implemented as server-side scripts that:

  1. Query participant data through the LAMP API.
  2. Evaluate conditions or run algorithms.
  3. Take actions (send notifications, schedule activities, update tags).

Interventions run as external clients of the API — they do not modify the core platform. See Cron Jobs for scheduling recurring intervention checks.

Considerations​

  • Ensure proper IRB approval and consent for automated interventions.
  • Document intervention logic and decision rules.
  • Include safety checks and escalation paths.
  • Test thoroughly before deploying to participants.