You are interviewing for a health-tech product analytics role. Assume the following table contains one row per appointment with its final status. **Table: `appointments`** - `appointment_id` (BIGINT, primary key) - `user_id` (BIGINT, not null) - `scheduled_start_at` (TIMESTAMP, not null) — when the appointment was scheduled to start - `status` (VARCHAR, not null) — one of: `'cancelled'`, `'returned'`, `'confirmed'`, `'completed'`, `'no_show'` - `status_updated_at` (TIMESTAMP, not null) — when the final `status` was set **Definitions / assumptions** - All timestamps are in UTC. - A user can have multiple appointments. - A user’s **first appointment** is the appointment with the earliest `scheduled_start_at` (break ties by smallest `appointment_id`). - A **first-cancelled user** is a user whose first appointment has `status = 'cancelled'`. - A user is considered to **have another future returned/confirmed appointment** if they have any appointment with `scheduled_start_at` strictly after their first appointment’s `scheduled_start_at` and with `status IN ('returned','confirmed')`. **Task** Write a SQL query to compute the **percentage of first-cancelled users who never have another future returned/confirmed appointment**. **Required output (single row)** - `first_cancelled_users` (integer) - `never_returned_confirmed_users` (integer) - `pct_never_returned_confirmed` (decimal between 0 and 1) (You may use CTEs and window functions.)