Evidence map›Paper›PMID 38094576›Full record

ArticleThe EPMA journal2023

Development and validation of a short-form suboptimal health status questionnaire.

Shuyu Sun, Hongzhi Liu, Zheng Guo, Qihua Guan, Yinghao Wang, Jie Wang, Yan Qi, Yuxiang Yan, Youxin Wang, Jun Wen and 2 more

Open access · greenAbstract read
In one paragraph

Article in The EPMA journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
4.2field-weighted citation impact, top 5% of its field
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

15 citing papers in PubMed, 19 citations in OpenAlex.

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  14. Mlp4green: A Binary Classification Approach Specifically for Green Odor.International journal of molecular sciences · 2024
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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

12 authors at 6 institutions in 3 countries.

Shuyu Sun *School of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China.
Hongzhi Liu *School of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China.
Zheng Guo *Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN USA.
Qihua GuanSchool of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China.
Yinghao WangSchool of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China.
Jie WangSchool of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China.
Yan QiSchool of Rehabilitation and Nursing, Yunnan Medical Health College, Kunming, China.
Yuxiang YanBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China.
Youxin WangBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China.
Jun WenCentre for Precision Health, Edith Cowan University, Perth, Australia.
Haifeng HouSchool of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China.ORCID 0000-0002-1131-1619
Suboptimal Health Study Consortium
Shandong First Medical University · CNCapital Medical University · CNAffiliated Hospital of Taishan Medical University · CNEdith Cowan University · AUKunming Medical University · CNVanderbilt University Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Suboptimal health status (SHS) is a reversible, borderline state between optimal health and disease. Although this condition's definition is widely understood, related questionnaires must be developed to identify individuals with SHS in various populations relative to predictive, preventive, and personalized medicine (PPPM/3PM). This study presents a short-form suboptimal health status questionnaire (SHSQ-SF) that appears to possess sufficient reliability and validity to assess SHS in large-scale populations. Methods: A total of 6183 participants enrolled from Southern China constituted a training set, while 4113 participants from Northern China constituted an external validation set. The SHSQ-SF includes nine key items from the Suboptimal Health Status Questionnaire-25 (SHSQ-25), an instrument that has been applied to Africans, Asians, and Caucasians. Item analysis and reliability and validity tests were carried out to validate the SHSQ-SF. The receiver operating characteristic (ROC) curve was used to identify an optimal cutoff value for SHS diagnosis, by which the area under the curve (AUC) and 95% confidence interval (CI) were determined. Results: Cronbach's α coefficient for the training dataset was 0.902; the split-half reliability was 0.863. The Kaiser-Meyer-Olkin (KMO) value was 0.880, and Bartlett's test of sphericity was significant ( Conclusions: We developed a short form of the SHS questionnaire that demonstrated sound reliability and validity when assessing SHS in Chinese residents. From a PPPM/3PM perspective, the SHSQ-SF is recommended for the rapid screening of individuals with SHS in large-scale populations. Supplementary Information: The online version contains supplementary material available at 10.1007/s13167-023-00339-z.

Indexed as

Large-scale population screeningPredictive preventive and personalized medicine (PPPM / 3PM)QuestionnaireReliabilitySuboptimal health status (SHS)Validity

Identifiers

PMID38094576
PMCPMC10713892
OpenAlexW4386650585

What OpenQuestion holds

Textmetadata
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.