AST Tracker

Turn theory into practice. Measure your environment, track your mood, and contribute to real science.

The AST Tracker is a mobile and web app built to record the core variables of Affective Socialization Theory in everyday life. It helps people understand how context shapes emotional regulation and agency while producing anonymous, aggregated data that can test and improve AST hypotheses.

How It Works: The Two Main Activities

Daily Check-ins

  • Log current mood through valence and arousal.
  • Select the immediate context, such as home, work, or social setting.
  • Build a personal Mood Stability Index (MSI) over time.
  • Record acute events (panic, conflict, shocks) separately to preserve long-term trends.

Weekly Reviews

  • Rate each key context on clarity (K), consistency (S), agency (A), and quality (Q).
  • Log Material Strain (MAT) pressures and how intensely they were felt.
  • Track progress on behavioral goals through BCI.
  • Set your next-week Agency Expectancy (AE) forecast.

This cadence directly mirrors the AST mathematical framework: daily state signals plus weekly structural inputs.

What the App Measures: Key Variables

  • MAT (Material Strain): Combines objective survival pressures (housing, food, healthcare, and related constraints) with subjective worry intensity. AST predicts that when MAT exceeds the provisional threshold of 15, learning and neuroplastic adaptation are blocked until conditions improve.
  • MSI (Mood Stability): Derived from week-to-week variability in daily mood logs. Higher MSI reflects a steadier emotional baseline, which AST treats as a prerequisite for sustained agency.
  • SED (Socialization Exposure Dose): Quality-adjusted context exposure, approximated as hours × clarity × consistency × agency. This represents how strongly each environment conditions behavior and affect.
  • BCI (Behavioral Control): A weekly measure of follow-through on chosen goals, such as exercise, study, or reducing harmful habits.
  • AE (Agency Expectancy): A forward-looking estimate of whether your actions will matter in the coming week; this is a key predictor of future effort and persistence.
  • Context-level scores (HMC, CCC, HV): With explicit opt-in consent, anonymous aggregates estimate rule clarity (HMC), cooperative versus coercive character (CCC), and instability (HV) for shared contexts.

The Science Inside the App

After each weekly review, the app applies AST equations to estimate likely changes in mood stability and behavioral control given your recent inputs. The following week, predicted and observed outcomes can be compared. That comparison is the core of empirical testing: each user becomes a repeated-case validation cycle.

If MAT crosses threshold, the app marks learning as likely blocked. If context indicators suggest coercion (low CCC) or instability (high HV), it can flag structural friction that may be undermining effort. These outputs are provisional hypotheses, not diagnoses. Their purpose is to help users notice patterns and ask better questions.

Hypothesis Highlight

AST Tracker treats model coefficients as updateable research parameters. Predictions are transparent prompts for observation, not fixed verdicts.

Privacy and Consent Model

Anonymous IDs

Each user receives a random pseudonymous identifier. No email address or phone number is required for core tracking.

No Text Logs Uploaded

Free-text notes, custom context names, and precise timestamps remain on device.

Opt-in Sharing

Contributing weekly scores to the global dataset is optional and revocable at any time.

Data Ownership

You can export your full history or delete local and server-side data in one action.

AST Tracker is designed as a research instrument that respects participant autonomy, not as a surveillance system.

Goals of the Tracker

  • Personal insight: reveal how environments influence mood and agency over time through trend dashboards and pattern summaries.
  • Collective validation: test AST claims around MAT thresholds, HMC/CCC/HV moderation, and recursive feedback loops.
  • Community science: support co-research, where participant data refines equations and strengthens explanatory power.

The long-term aim is to show that what we call mental health is also a signal about environmental quality and structure.

Current Status & Next Steps

AST Tracker is in active development, with beta testing planned across iOS, Android, and the web experience.

iOS Beta (Coming Soon) Android App: Still in Testing — Join the Google Group Web App (www.asttracker.com)

Android access is currently limited to testers. To join testing, request access in the Google Group linked above.

Read the AST papers and research notes.

Download the app and start tracking your environment today.

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