Data Processing Apparatus for Caregiver Mental Health Screening
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Solution Overview
Problem
Current methods for identifying postpartum depression in caregivers, such as mothers, often fail to reach those who do not participate in risk screening, leading to overlooked cases of developing or potential depression.
Innovation Solution
A data processing apparatus and method that analyzes child-care data to determine if a caregiver needs to undergo examination for mental health issues, sends notifications for questionnaires, and assesses the risk based on responses, facilitating early detection and support.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If risk screening is conducted through questionnaires, then postpartum depression can be detected, but parents may overlook the examination if they do not have an opportunity to participate
Solution Approach 1:
The system performs preliminary analysis of child-care data before conducting the examination, automatically identifying caregivers who need screening based on their child-care patterns. This preliminary action ensures that only relevant caregivers are selected for examination, preventing missed cases while maintaining detection accuracy.
Solution Approach 2:
The system continuously monitors child-care data and provides feedback by automatically triggering examinations when abnormal patterns are detected. This feedback mechanism ensures that caregivers who show signs of distress are promptly identified and examined, eliminating the opportunity loss present in traditional manual screening systems.
2Measurement precision
If manual risk screening is performed, then postpartum depression can be identified, but the process requires active participation from parents which is not always guaranteed
Solution Approach 1:
The system automatically analyzes child-care data and triggers examinations without requiring active participation from parents. The examination process is initiated automatically when the system detects patterns indicating potential postpartum depression, making the screening process self-service oriented and eliminating the burden of manual participation while maintaining screening accuracy.
Solution Approach 2:
The system replaces the mechanical manual questionnaire distribution and collection process with an automated digital system that analyzes child-care data and electronically administers examinations. This substitution maintains measurement precision while dramatically improving ease of operation by eliminating the need for active parental initiation.
3Loss of time
If automated analysis of child-care data is performed, then early detection of postpartum depression is enabled, but the system complexity increases
Solution Approach 1:
The system segments the detection process into distinct modules: child-care data collection, automated analysis for pattern recognition, automatic examination triggering, and result processing. This segmentation enables early detection through continuous monitoring while managing system complexity by organizing functions into independent, manageable components that can be implemented incrementally.
Data Source
AI summary
A data processing apparatus according to an embodiment includes: a storage unit that stores child-care data indicating details of child care of a caregiver; a first determination unit that performs analysis on the child-care data stored in the storage unit and determines whether or not an examination has to be conducted on whether or not the caregiver suffers from a mental disease or is at risk of disease, based on a result of the analysis; a notification unit that makes a notification for requesting answers to questions for the examination to the caregiver, when the first determination unit determines that the examination has to be conducted, an acquisition unit that acquires the answer to the question for the examination from the caregiver who had the notification from the notification unit; and a second determination unit that determines whether or not the caregiver suffers from a disease or is at risk of disease, based on the answers acquired by the acquisition unit.