# A Quantitative Text Analysis of the 8050 Problem and Stratified Support in the Japanese Diet

## TL;DR

This study uses text analysis to show how Japan's legislative language on elderly caregivers and socially withdrawn adults shifted from clinical to administrative focus after a 2020 policy change.

## Contribution

The paper introduces full-population parliamentary text analysis to quantify semantic shifts in public health policy discourse.

## Key findings

- Mentions of 'hikikomori' (clinical reality) peaked in 2019 but declined after 2020.
- Post-2020, administrative terms like 'Stratified Support' and 'cooperation' dominated legislative discourse.
- Outcome-oriented clinical terms were scarce compared to procedural language in policy debates.

## Abstract

Introduction

The "8050 problem," referring to households where elderly parents in their 80s support socially withdrawn (hikikomori) children in their 50s, presents a critical public health challenge in Japan. To address such complex social isolation, the Japanese government introduced the "Stratified Support System" in 2021. However, there is a concern that bureaucratic framing may obscure the clinical urgency of the issue. This study employs full-population text analysis to objectively quantify the semantic shift in Japanese legislative discourse regarding the 8050 problem, specifically determining whether the 2020 Social Welfare Act amendment drove a transition from clinical terminology to administrative procedural framing.

Materials and methods

I conducted a comprehensive quantitative text analysis of all minutes from the Japanese National Diet (both the House of Representatives and House of Councillors) over an 11-year period (January 1, 2015, to December 31, 2025). Utilizing the National Diet Library Application Programming Interface (NDL API) to eliminate selection bias, I targeted the entire population of parliamentary statements in Japan. I employed Python-based (Python Software Foundation, Wilmington, DE) natural language processing (NLP) with the morphological analyzer "Janome." I performed a time-series analysis of keyword frequency and co-occurrence network analysis to visualize the semantic structure of policy debates, ensuring their high reproducibility.

Results

Time-series analysis revealed a significant paradigm shift: mentions of "hikikomori" (clinical reality) peaked in 2019 but diminished significantly after 2020. Conversely, mentions of "Stratified Support" (administrative logic) surged after the 2020 Social Welfare Act amendment. The co-occurrence analysis of the new system's discourse demonstrated a dominance of procedural terms such as "cooperation," "consultation," and "system." Notably, outcome-oriented terms related to clinical recovery or the direct resolution of isolation were scarce compared to administrative process terminology.

Conclusions

Legislative discourse on social withdrawal has shifted from clinical realities to administrative coordination. This "depersonalization" of policy language may risk prioritizing institutional maintenance over the direct resolution of social determinants of health (SDOH). While administrative integration is necessary, the findings suggest a potential disconnect between policy frameworks and the lived experiences of vulnerable populations. API-based full-text analysis serves as a vital objective tool for monitoring structural shifts in public health policy.