Evidence map›Paper›PMID 42245360›Full record

ArticleFrontiers in public health2026

Financial strain, digital health reliance, and medical preferences: a multi-dimensional analysis of Chinese residents.

Hejing Zhang, Yunchao Cai, Xuao Chen

Abstract read
In one paragraph

Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Hejing ZhangSchool of Economics and Management, Ankang University, Ankang, China.
Yunchao CaiSchool of Economics and Management, Ankang University, Ankang, China.
Xuao ChenSchool of Economics and Management, Ankang University, Ankang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: While the link between financial strain and poor health is well-established, research remains fragmented across isolated indicators and lacks an integrated understanding of how resource scarcity reshapes health-seeking strategies, particularly the use of digital resources and traditional medical systems in non-Western contexts. Methods: Utilizing data from the 2021 China General Social Survey (CGSS), this study examines the relationship between financial strain and three connected domains. The empirical analysis employs Ordinary Least Squares (OLS) regression models to analyze two independent sub-samples of working-age respondents ( Results: Regression analyses reveal that financial strain is a pervasive stressor that compromises multiple domains of well-being and is associated with significantly lower preventative health investments. In the digital sphere, financial strain is closely linked to a unique reliance on internet-based health resources, which is often accompanied by a lack of regard for information reliability. Moreover, financial strain is significantly associated with a stronger cognitive preference for, and greater behavioral utilization of, Traditional Chinese Medicine (TCM). Discussion: These findings highlight a unique adaptation strategy where individuals navigate resource scarcity by leveraging digital tools and traditional medical systems. These results have critical implications for health equity, underscoring the need for policies that address digital health literacy and integrate culturally trusted systems into formal primary care.

Indexed as

Digital HealthFinancial StressPatient Acceptance of Health CarePatient PreferenceAdultChinaDigital MediaFemaleHumansMaleMedicine, Chinese TraditionalMiddle AgedSurveys and QuestionnairesChinadigital health reliancefinancial strainhealth related outcomemedical preferences

Identifiers

PMID42245360
PMCPMC13230075

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Registered trials

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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.