# Mood Tracking

Mood Tracking allows your application to record how a user is feeling each day and retrieve their emotional history over time. This creates a lightweight wellbeing timeline that can support recommendations, insights, and personalised user experiences.

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### **What Mood Tracking Provides**

therappai offers a simple and reliable system for capturing emotional state:

* **Mood rating** (numeric scale)
* **Optional notes**
* **Timestamped entries**
* **Historical mood logs**
* **Aggregated summaries (daily, weekly, monthly)**

The system is designed to be flexible so you can build your own UI and visualisations.

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### **How Mood Tracking Works**

Every time a user submits a mood check-in, your app sends:

* a number (e.g., 1–5 or 1–10 scale)
* optional text describing how they feel
* optional context (stress, sleep quality, triggers)

The API stores the entry and associates it with that user.

You can then query:

* **all mood entries**
* **entries over a specific time period**
* **latest mood**
* **trend summaries**

This supports dashboards, streaks, calendars, reflection tools, or progress screens.

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### **Typical Use Cases**

Developers commonly use Mood Tracking to:

* Show a **daily mood check-in prompt**
* Generate **mood charts or heatmaps**
* Trigger **content recommendations** (e.g., CBT tools, mindfulness)
* Track user **improvement or decline over time**
* Personalise AI therapy sessions
* Provide **emotional insights** in account dashboards

Because mood entries are lightweight, they work well for both mobile and web apps.

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### **Fetching Mood History**

Your application can retrieve:

* all logs
* logs within a specific range
* logs grouped by day/week/month
* the user’s most recent check-in

This enables you to build:

* historical graphs
* wellbeing timelines
* emotional summaries
* personalised interventions

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### **Insights & Trends**

While the API currently returns raw mood data, you can easily build your own insights or pair mood history with:

* **AI therapy suggestions**
* **Content recommendations**
* **Daily routines**
* **Sleep and stress questionnaires** (if you collect additional info)

Future versions of the API may include built-in trend analysis.

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### **Combining Mood Tracking With Other Features**

Mood Tracking works best when used alongside:

#### **AI Therapy**

Use recent mood patterns to guide the conversation or tailor support.

#### **Content Library**

Recommend CBT, DBT, or mindfulness exercises based on lows, spikes, or patterns.

#### **Daily Tasks**

Generate tasks or reminders when mood declines.

#### **Crisis Buddy**

If a user logs a concerning mood, your UI can surface crisis support options.