Evidence map›Paper›PMID 39572757›Full record

ArticleScientific reports2024

Health knowledge needs of administrative staff and related influencing factors: a cross-sectional data from Yuxi, China.

Lin-Sen Feng, Ai Tang, Hao-Yu Wang, Yi-Xiao Song, Qing Yang, Jia-Qi Xie, Lu-Ya Chu, Si-Rong She, Zheng-Jiao Dong, Ruo-Yu Yan

Abstract read
In one paragraph

Article in Scientific reports, 2024. 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
–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

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

10 authors.

Lin-Sen FengThe Sixth Affiliated Hospital of Kunming Medical University (The People's Hospital of Yuxi City), No.21, Nie Er Road, Hongta District, Yuxi, 653100, Yunnan, China.ORCID 0000-0003-0329-9936
Ai TangSchool of General Practitioners, Kunming Medical University, Yuxi, Yunnan, China.ORCID 0009-0004-0215-449X
Hao-Yu WangSchool of Basic Medicine, Kunming Medical University, Kunming, Yunnan, China.ORCID 0009-0001-5683-9943
Yi-Xiao SongSchool of Forensic Medicine, Kunming Medical University, Kunming, Yunnan, China.
Qing YangYiliang County Center for Disease Control and Prevention, Zhaotong, Yunnan, China.
Jia-Qi XieSchool of Basic Medicine, Kunming Medical University, Kunming, Yunnan, China.
Lu-Ya ChuSchool of Basic Medicine, Kunming Medical University, Kunming, Yunnan, China.
Si-Rong SheThe First School of Clinical Medicine, Kunming Medical University, Kunming, Yunnan, China.
Zheng-Jiao DongThe Sixth Affiliated Hospital of Kunming Medical University (The People's Hospital of Yuxi City), No.21, Nie Er Road, Hongta District, Yuxi, 653100, Yunnan, China. dzj0912@163.com.ORCID 0000-0003-0997-5595
Ruo-Yu YanThe Sixth Affiliated Hospital of Kunming Medical University (The People's Hospital of Yuxi City), No.21, Nie Er Road, Hongta District, Yuxi, 653100, Yunnan, China. 493843454@qq.com.

Funding

National Training Program of Innovation and Entrepreneurship for Undergraduates 202410678049Program of Philosophy and Social Science Foundation of Yunnan Province QN202214
6 · The paper itself

Abstract

Lack of health knowledge can be a main cause of barriers to early diagnosis and treatment, and it can also highlight the deficiencies in health education. Therefore, it is essential to understand the health knowledge needs of individuals and the related influencing factors in order to improve health education models. A total of 935 administrative staff (AS) were selected as study participants by convenience sampling in Yuxi City, China. An electronic questionnaire, comprising four parts-Health Knowledge Needs, Sociodemographic Characteristics, Health Psychology and Behavior, and Self-Reported Medical History-were used to collect data. Statistical analysis was conducted using an internal consistency test, Kruskal-Wallis test, principal component analysis, hierarchical clustering analysis, and binary logistic regression analysis, performed with SPSS version 19.0. The Health Knowledge Needs Questionnaire had a Cronbach's α of 0.883 and a Guttman Split-Half coefficient of 0.907. The need rates for health knowledge exceeding 30% are as follows: Traditional Chinese Medicine, Hypertension, Weight Management, Dietary Nutrition and Food Hygiene, Hyperlipidemia, Gastrointestinal Diseases, Heart Diseases, and First Aid. Health knowledge needs were summarized into six dimensions: "Diseases with Low Health Knowledge Needs", "Maternal and Child Health Care and Thyroid Diseases", "Cardiovascular and Cerebrovascular Diseases and Malignancies", "Health Preservation and First Aid", "The Four Highs Syndrome", and "Respiratory and Digestive Diseases". Gender, self-rated economic pressure, family size, and self-reported number of diseases were identified as influencing factors of health knowledge needs (P < 0.05). Thus, precision health education should be conducted according to the health knowledge needs of the target group, and various health knowledge topics should be organically integrated into modular health education to improve its efficiency.

Indexed as

Health Knowledge, Attitudes, PracticeAdultChinaCross-Sectional StudiesFemaleHealth EducationHumansMaleMiddle AgedSurveys and QuestionnairesAdministrative staffDiseaseHealth educationHealth knowledge needsHealth literacy

Identifiers

PMID39572757
PMCPMC11582627

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.