ArticleBMC research notes2026
Dataset on service access, socio‑economic status, and rehabilitation needs among persons with disabilities in China.
Article in BMC research notes, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
objectivesThe dataset was collected to provide a comprehensive overview of service utilization, socio-economic conditions, and rehabilitation needs among registered persons with disabilities in Changchun, China. It aims to address the lack of large-scale, individual-level data in this field and to support research on disability inclusion, welfare systems, and social policy development. DATA DESCRIPTION: The dataset contains records for 197,302 registered persons with disabilities gathered in 2020 via telephone interviews supplemented by in-person visits. It comprises 155 variables across seven domains: demographics; economic conditions; internet access and use; employment and skills; medical and rehabilitation services and assistive products and technology; accessible environment; and cultural and sports participation. Anonymized data, raw tables, and a detailed codebook are openly available on Harvard Dataverse [15]. The resource enables fine-grained analyses of urban-rural and district heterogeneity, functional-limitation patterns, and gaps between required and received services. It also supports the construction of equity-sensitive indicators, multivariable and multilevel models of service utilization, and benchmarking for programmed monitoring. The cross-sectional design and a focus on certificate holders should be considered when interpreting results, yet the scale and coverage make the dataset valuable for comparative studies and careful linkage with public statistics under appropriate safeguards.
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Registered trials
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.