Evidence map›Paper›PMID 40241090›Full record

ArticleInternational journal for equity in health2025

A data-driven approach to detect support strategies for children living in households receiving public assistance in Japan: a mixed methods study to establish tailor-made health and welfare care.

Keiko Ueno, Daisuke Nishioka, Shiho Kino, Naoki Kondo

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Article in International journal for equity in health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Keiko UenoDepartment of Social Epidemiology, Graduate School of Medicine and School of Public Health, Science Frontier Laboratory, Kyoto University, Floor 2, Science Frontier Laboratory, Yoshida-konoe-cho, Sakyo-ku, Kyoto-shi, Kyoto, 606 - 8315, Japan. ueno.keiko.6s@kyoto-u.ac.jp.
Daisuke NishiokaDepartment of Medical Statistics, Research & Development Center, Osaka Medical and Pharmaceutical University, Osaka, Japan.
Shiho KinoDepartment of Preventive Oral Health Care Sciences, Graduate School of Medical and Dental Sciences, Institute of Science Tokyo, Tokyo, Japan.
Naoki KondoDepartment of Social Epidemiology, Graduate School of Medicine and School of Public Health, Science Frontier Laboratory, Kyoto University, Floor 2, Science Frontier Laboratory, Yoshida-konoe-cho, Sakyo-ku, Kyoto-shi, Kyoto, 606 - 8315, Japan.

Funding

Japan Society for the Promotion of Science 17K19793Japan Society for the Promotion of Science 22K21081JST RISTEX JPMJRX21K6
6 · The paper itself

Abstract

backgroundChild poverty adversely affects children's health and social lives. Children in households receiving public assistance have diverse needs regarding their health and lives Therefore, they require tailored support interventions based on individual sociodemographic backgrounds and other personal attributes. However, to the best of our knowledge, no study has identified distinct segments of these children using self-reported data or evaluated the health and social support strategies for the obtained segments. This study aimed to apply a clustering technique to quantitatively identify the distinct segments among children in households receiving public assistance, qualitatively describe the segment characteristics, and suggest potentially effective health and social life support strategies for each segment.

methodsIn the quantitative phase, we used the probabilistic latent semantic analysis (PLSA), a machine learning-based soft clustering method, to identify the segments of children aged 10-15 years in households receiving public assistance. We used the segments obtained in the quantitative phase to subsequently conduct seven semi-structured interviews and one focus group with professionals supporting children with complex needs. The interviewees were asked to describe the segment characteristics and propose health and social life support strategies for each segment.

resultsIn total, 1,275 children were included in the quantitative analysis. PLSA identified all the segments with distinct characteristics that made sense to professionals who supported children in households receiving public assistance, confirmed by qualitative findings: e.g. "children who can do things on their own" (Segment 1), "children living in a facility" (Segment 2), "children who are in hikikomori (social withdrawal)" (Segment 3), "children who cannot be bothered to answer conceptual questions about themselves" (Segment 4), and "children from households with intergenerational public assistance use" (Segment 5). The qualitative findings also suggested various support measures not only for physical health but also for the social and mental health of children in households receiving public assistance, for example, "financial support for higher education" for Segment 1, and "whole family support" for Segment 5.

conclusionsChildren in households receiving public assistance can be categorized into distinct segments and would consequently benefit from tailored support strategies for their health and social lives.

Indexed as

Public AssistanceSocial SupportAdolescentChildFamily CharacteristicsFemaleFocus GroupsHumansJapanMalePovertyQualitative ResearchSocial WelfareChild healthMixed methods studyPublic assistanceSegmentationSoft clusteringTailored support

Identifiers

PMID40241090
PMCPMC12004781

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.