{
  "format": "dataset-manifest/1",
  "slug": "mental-health-support-app",
  "version": 3,
  "seed": "mental-health-support-app:1",
  "engine": 1,
  "engineVersion": "1.0.0",
  "spec": {
    "format": "dataset/1",
    "slug": "mental-health-support-app",
    "name": "Mental Wellness Insights",
    "tagline": "Users, therapists, mood logs, activities, and engagement metrics from a mental health support platform.",
    "description": "Users track their moods and engage with various mental wellness activities on a dynamic platform that connects them with therapists. Each user creates a profile in the users table, where their unique characteristics, habits, and preferences are recorded. They can also log their mood over time in the mood_logs table, providing crucial insight into their emotional journey. Meanwhile, the therapists table includes professionals who offer guidance and support, detailing their qualifications and specialties, creating a bridge for users seeking help. To foster personal growth, users can engage in activities listed in the activities table, which outlines different therapeutic exercises designed to enhance mental health and well-being.\n\nEach interaction within this platform is tied together through relational data. For example, each mood log entry is associated with a specific user, enabling trends and patterns to be identified over time. The engagement_metrics table captures overall user interaction with the platform, including goal completion rates and participation in group discussions, highlighting how users are capitalizing on the available resources. This connectivity allows developers to explore complex relationships between users, their mood trends, and the effectiveness of various activities.\n\nQuestions that can be answered using this data include: How do users’ moods fluctuate over time in relation to their engagement in activities? What types of activities correlate with higher therapist engagement levels? Are there specific demographics that show different engagement patterns? Analyzing this synthetic data provides a playground for developers to practice building queries, generating insights, and creating visualizations that can inform mental wellness strategies, ultimately aiding the understanding of user behavior in a supportive environment.",
    "domain": "customer-support",
    "shape": "ledger",
    "useCases": [
      "sql-practice",
      "teaching"
    ],
    "keywords": [
      "mental health",
      "user engagement",
      "therapy",
      "mood tracking",
      "support platform"
    ],
    "locale": "en",
    "license": "CC0-1.0",
    "version": 1,
    "tables": {
      "users": {
        "description": "A table of users who participate in the mental wellness platform. Each row represents a unique user with their details.",
        "rows": 300,
        "columns": {
          "user_id": {
            "kind": "pk",
            "description": "Unique identifier for each user."
          },
          "full_name": {
            "kind": "fullName",
            "description": "Full name of the user."
          },
          "email": {
            "kind": "email",
            "from": "full_name",
            "description": "Email address of the user."
          },
          "join_date": {
            "kind": "date",
            "from": "2020-01-01",
            "to": "2023-12-31",
            "description": "Date the user joined the platform.",
            "trend": "growing"
          },
          "active": {
            "kind": "bool",
            "trueRate": 0.8,
            "description": "Whether the user is currently active on the platform."
          }
        }
      },
      "therapists": {
        "description": "A table of therapists available on the platform. Each row represents a unique therapist.",
        "rows": 100,
        "columns": {
          "therapist_id": {
            "kind": "pk",
            "description": "Unique identifier for each therapist."
          },
          "full_name": {
            "kind": "fullName",
            "description": "Full name of the therapist."
          },
          "specialization": {
            "kind": "enum",
            "values": [
              "CBT",
              "DBT",
              "Mindfulness",
              "Psychoanalysis"
            ],
            "description": "Therapeutic specialization of the therapist.",
            "nullable": true,
            "weights": [
              6,
              2,
              1,
              1
            ]
          },
          "availability": {
            "kind": "bool",
            "trueRate": 0.7,
            "description": "Whether the therapist is currently available for sessions.",
            "nullable": true,
            "when": {
              "column": "specialization",
              "in": [
                "CBT",
                "DBT",
                "Mindfulness",
                "Psychoanalysis"
              ]
            }
          }
        }
      },
      "mood_logs": {
        "description": "A table tracking users' mood over time. Each row represents a mood entry by a user.",
        "rows": 1000,
        "columns": {
          "log_id": {
            "kind": "pk",
            "description": "Unique identifier for each mood log entry."
          },
          "user_id": {
            "kind": "fk",
            "ref": "users.user_id",
            "description": "Foreign key linking to the user."
          },
          "mood": {
            "kind": "enum",
            "values": [
              "happy",
              "sad",
              "anxious",
              "calm"
            ],
            "weights": [
              0.4,
              0.3,
              0.2,
              0.1
            ],
            "description": "Mood of the user at the time of logging."
          },
          "log_date": {
            "kind": "date",
            "from": "2020-01-01",
            "to": "2023-12-31",
            "description": "Date when the mood was logged.",
            "nullable": true,
            "when": {
              "column": "mood",
              "in": [
                "happy",
                "sad",
                "anxious",
                "calm"
              ]
            },
            "trend": "seasonal"
          },
          "mood_intensity": {
            "kind": "int",
            "min": 1,
            "max": 10,
            "distribution": "normal",
            "description": "Intensity of the mood on a scale from 1 to 10."
          },
          "duration_minutes": {
            "kind": "int",
            "min": 1,
            "max": 1440,
            "distribution": "normal",
            "description": "Duration in minutes that the mood was felt."
          }
        }
      },
      "activities": {
        "description": "A table of activities that users can engage in to improve their mental wellness. Each row represents an activity.",
        "rows": 50,
        "columns": {
          "activity_id": {
            "kind": "pk",
            "description": "Unique identifier for each activity."
          },
          "name": {
            "kind": "title",
            "description": "Name of the activity.",
            "nullable": true,
            "pool": [
              "meditation",
              "yoga",
              "journaling",
              "breathing",
              "exercise",
              "walking",
              "reading",
              "painting",
              "gardening",
              "cooking",
              "dancing",
              "running",
              "hiking",
              "stretching",
              "fishing",
              "knitting",
              "singing",
              "crafting",
              "volunteering",
              "traveling",
              "photography",
              "biking",
              "writing",
              "listening",
              "relaxing",
              "exploring",
              "playing",
              "meditative",
              "mindfulness",
              "self-care",
              "nature-walk",
              "goal-setting",
              "community-service",
              "therapy",
              "support-group",
              "workshop",
              "seminar",
              "retreat",
              "mind-mapping",
              "coaching",
              "counseling",
              "affirmations",
              "visualization",
              "aromatherapy",
              "pet-therapy",
              "music-therapy",
              "dance-therapy",
              "art-therapy",
              "drama-therapy"
            ],
            "min": 1,
            "max": 3
          },
          "type": {
            "kind": "enum",
            "values": [
              "exercise",
              "meditation",
              "journaling",
              "discussion"
            ],
            "description": "Type of activity.",
            "weights": [
              5,
              4,
              3,
              2
            ]
          },
          "difficulty": {
            "kind": "enum",
            "values": [
              "easy",
              "medium",
              "hard"
            ],
            "description": "Difficulty level of the activity.",
            "nullable": true,
            "when": {
              "column": "type",
              "in": [
                "exercise",
                "meditation",
                "journaling",
                "discussion"
              ]
            }
          }
        }
      },
      "engagement_metrics": {
        "description": "A table capturing the engagement of users with the platform's features. Each row represents engagement metrics for a user.",
        "rows": 300,
        "columns": {
          "engagement_id": {
            "kind": "pk",
            "description": "Unique identifier for the engagement record."
          },
          "user_id": {
            "kind": "fk",
            "ref": "users.user_id",
            "description": "Foreign key linking to the user."
          },
          "activities_completed": {
            "kind": "int",
            "min": 0,
            "max": 20,
            "description": "Number of activities completed by the user.",
            "nullable": true,
            "distribution": "long-tail"
          },
          "sessions_attended": {
            "kind": "int",
            "min": 0,
            "max": 15,
            "description": "Number of therapy sessions attended by the user.",
            "nullable": true,
            "distribution": "long-tail"
          },
          "last_engagement_date": {
            "kind": "date",
            "from": "2020-01-01",
            "to": "2023-12-31",
            "description": "Date of the last engagement with the platform.",
            "trend": "growing"
          }
        }
      }
    },
    "structure": "multi-table",
    "traits": [
      "nullable",
      "timestamped",
      "categorical"
    ],
    "analysisQuestions": [
      "What is the average mood logged by users over time?",
      "How do different activities correlate with mood improvement?",
      "What percentage of users actively engage in group discussions?",
      "Which therapists have the highest engagement rates among users?"
    ],
    "suggestedQueries": [
      {
        "title": "Get all active users",
        "sql": "SELECT * FROM users WHERE active = TRUE;",
        "dialect": "postgres"
      },
      {
        "title": "Count mood logs by mood type",
        "sql": "SELECT mood, COUNT(*) FROM mood_logs GROUP BY mood;",
        "dialect": "postgres"
      },
      {
        "title": "Average activities completed by active users",
        "sql": "SELECT AVG(activities_completed) FROM engagement_metrics WHERE user_id IN (SELECT user_id FROM users WHERE active = TRUE);",
        "dialect": "postgres"
      },
      {
        "title": "Users' last engagement dates",
        "sql": "SELECT u.full_name, e.last_engagement_date FROM users u JOIN engagement_metrics e ON u.user_id = e.user_id;",
        "dialect": "postgres"
      }
    ],
    "usageScenarios": [
      {
        "title": "Data Analysis for Mental Health Research",
        "body": "Researchers can use this dataset to analyze trends in user engagement and mood over time, helping to identify effective therapeutic activities and support strategies."
      },
      {
        "title": "Training SQL Skills",
        "body": "Developers and data analysts can practice their SQL skills by querying this dataset, gaining experience with joins, aggregates, and subqueries relevant to customer support contexts."
      },
      {
        "title": "Teaching Data Literacy",
        "body": "Educators can use this dataset to teach data literacy concepts, showing students how to analyze user behavior data and derive insights that can inform mental health support strategies."
      },
      {
        "title": "Application Development for Mental Wellness",
        "body": "Software developers can utilize this dataset to build applications that track user wellness activities, mood logging, and therapist interactions, enhancing mental health support tools."
      }
    ]
  },
  "counts": {
    "activities": 50,
    "therapists": 100,
    "users": 300,
    "engagement_metrics": 300,
    "mood_logs": 1000
  },
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