Evidence map›Paper›PMID 39975786›Full record

ArticleFrontiers in public health2025

Latent profile and determinants of self-management behaviors among older adult patients with chronic diseases: a cross-sectional study.

Yu Jiao Shao, Xiao Cui Duan, Xue Jun Xu, Hong Yan Guo, Ze Yu Zhang, Shuang Zhao, Fu Zhi Wang, Yong Xia Chen, Qin Chen, Shi Qing Zhang and 1 more

Abstract read
In one paragraph

Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 2 pooled it
–field-weighted citation impact
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

18 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  9. Treatment experience of patients with failedFrontiers in public health · 2026
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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

11 authors.

Yu Jiao ShaoSchool of Nursing, Bengbu Medical University, Bengbu, Anhui, China.
Xiao Cui DuanSchool of Nursing, Bengbu Medical University, Bengbu, Anhui, China.
Xue Jun XuSchool of Nursing, Bengbu Medical University, Bengbu, Anhui, China.
Hong Yan GuoDepartment of General Practice, First Affiliated Hospital, Bengbu Medical University, Bengbu, Anhui, China.
Ze Yu ZhangNursing Department, The 902nd Hospital of Joint Logistic Support Force of PLA, Bengbu, Anhui, China.
Shuang ZhaoNursing Department, First People's Hospital Affiliated with Bengbu Medical University, Bengbu, Anhui, China.
Fu Zhi WangSchool of Health Management, Bengbu Medical University, Bengbu, Anhui, China.
Yong Xia ChenNursing Department, First Affiliated Hospital, Bengbu Medical University, Anhui, China.
Qin ChenNursing Department, Suzhou Hospital Affiliated with Anhui Medical University, Suzhou, Anhui, China.
Shi Qing ZhangSchool of Nursing, Bengbu Medical University, Bengbu, Anhui, China.
Xiu Mu YangSchool of Nursing, Bengbu Medical University, Bengbu, Anhui, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To explore latent profiles of self-management behaviors in older adult patients with chronic diseases and identify the factors that influence different profiles, guiding targeted interventions. Methods: This study used convenience sampling to recruit 536 older adult patients with chronic diseases from three tertiary hospitals in Anhui Province between October 2023 and May 2024. Data were collected using a general information questionnaire, the age-adjusted Charlson Comorbidity Index (aCCI), the Chronic Disease Self-Management Behavior Scale, the Chronic Disease Management Self-Efficacy Scale, the Psychological Status Scale, the Digital Health Literacy Scale, and the Social Support Scale. Latent profile analysis was conducted using Mplus 8.3, and univariate and multivariate logistic regression analyses were performed using SPSS 26.0. Results: Three profiles of self-management behaviors emerged: "Low Self-Management" (50.2%), "High Exercise and Cognitive Management" (8.6%), and "Moderate Management with Enhanced Communication" (41.2%). Multivariate logistic regression revealed that residence, aCCI, number of digital devices used, perceived usefulness of digital health information, digital health literacy, social support, chronic disease management self-efficacy, and psychological status were significant factors affecting self-management profiles (all Conclusion: Self-management behaviors in older adult patients with chronic diseases were generally low, with substantial heterogeneity across profiles. Healthcare providers should tailor interventions based on the characteristics of each group to enhance self-management in digital health contexts.

Indexed as

Self-ManagementAgedAged, 80 and overChinaChronic DiseaseCross-Sectional StudiesFemaleHealth LiteracyHumansMaleMiddle AgedSelf EfficacySocial SupportSurveys and Questionnaireschronic diseasesdeterminantslatent profile analysisolder adultself-management

Identifiers

PMID39975786
PMCPMC11835868

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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.