Evidence map›Paper›PMID 35096099›Full record

ArticleEvidence-based complementary and alternative medicine : eCAM2021

Development and Validation of the Health Literacy Assessment Instrument for Patients with Chronic Pain.

Siqing Chen, Xingwei Zhang, Meijuan Cao, Bingyu Zhao, Jie Fang

Abstract read
In one paragraph

Article in Evidence-based complementary and alternative medicine : eCAM, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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

  1. Pooled it
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  4. Article
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

5 authors.

Siqing ChenCollege of Humanities, Zhejiang Dongfang Polytechnic, Wenzhou 325000, Zhejiang, China.
Xingwei ZhangDivision of Health Sciences, Hangzhou Normal University, Hangzhou 310036, Zhejiang, China.ORCID https://orcid.org/0000-0003-4126-5542
Meijuan CaoDivision of Health Sciences, Hangzhou Normal University, Hangzhou 310036, Zhejiang, China.ORCID https://orcid.org/0000-0002-6575-5936
Bingyu ZhaoDivision of Health Sciences, Hangzhou Normal University, Hangzhou 310036, Zhejiang, China.
Jie FangDivision of Health Sciences, Hangzhou Normal University, Hangzhou 310036, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A suitable health literacy assessment instrument for patients with chronic pain (HLCP) in China with good instrument's psychometric properties is required. A theoretical framework for the HLCP was developed by adopting the hierarchical model of health literacy proposed by Nutbeam. The reliability and validity of the HLCP were tested in a cross-sectional survey of 237 chronic pain patients from three pain clinics and wards of Grade-3A hospitals in Zhejiang Province, China. The discriminant degree method, correlation analysis method, factor analysis method (exploratory factor analysis), half reliability, and other methods were utilized to screen items for inclusion in the final version of HLCP, and the fitness of the model was subsequently evaluated by confirmatory factor analysis. Cronbach's alpha value and test-retest with two-week intervals were used to test the internal consistency and retest reliability of the HLCP. In the exploratory factor analysis, three domains, functional health literacy (10 items), interactive health literacy (14 items), and critical health literacy (7 items), comprising 31 items in total, were finally loaded; the model was determined to explain 70.9% of the total variance. HLCP's effective assessment of the health literacy level of patients with chronic pain and its acceptable reliability and validity were revealed through the results.

Identifiers

PMID35096099
PMCPMC8799325

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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.