Evidence map›Paper›PMID 42324520›Full record

ArticleBMC geriatrics2026

Pathways associated with hypertension self-management behaviors among older adults: a PRECEDE-PROCEED theory-guided path analysis.

Jin Li, Jin Cheng

Abstract read
In one paragraph

Article in BMC geriatrics, 2026. 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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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

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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

2 authors.

Jin LiChongqing Medical and Pharmaceutical College, Chongqing, China. 352366126@qq.com.
Jin ChengChongqing Medical and Pharmaceutical College, Chongqing, China.

Funding

Natural Science Research Project of Chongqing Medical and Pharmaceutical College YGZZKRC2025103
6 · The paper itself

Abstract

backgroundHypertension self-management is essential for reducing complications and maintaining functional well-being in later life, yet the multi-level factors associated with self-management among older adults remain insufficiently understood. This study investigated pathways linking predisposing, enabling, and reinforcing factors to hypertension self-management behaviors (HSMB) among older adults using a PRECEDE-PROCEED theory-guided model.

methodsA cross-sectional study was conducted from late March to early April 2026 among 264 older adults with hypertension in Chongqing, China. Data were collected through interviewer-administered structured questionnaires. Pearson correlation analysis and path analysis were used to examine direct and indirect associations among hypertension-related knowledge, self-efficacy, health education, healthcare resources and access, family support, and HSMB.

resultsSelf-efficacy and hypertension-related knowledge showed significant direct associations with HSMB. Healthcare resources and access demonstrated both direct and indirect associations with HSMB through knowledge and self-efficacy. Family support was associated with HSMB both directly and indirectly through healthcare resources and access, knowledge, and self-efficacy. Health education showed a negative indirect association with HSMB through knowledge, suggesting that the content, timing, or targeting of education may warrant closer examination.

conclusionsHSMB among older adults was associated with multi-level cognitive, environmental, and social factors. Self-efficacy, healthcare resources and access, and family support appeared to be particularly important correlates. Interventions for older adults with hypertension may benefit from combining skills-building, accessible services, and family-engaged support while improving the relevance and comprehensibility of health education.

Indexed as

Health Knowledge, Attitudes, PracticeHypertensionSelf-ManagementAgedAged, 80 and overChinaCross-Sectional StudiesFamily SupportFemaleHumansMaleSelf EfficacyHypertensionOlder adultsPath analysisPRECEDE–PROCEED modelSelf-management behaviors

Identifiers

PMID42324520
PMCPMC13536874

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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.