Evidence map›Paper›PMID 36654666›Full record

ArticleGeneral psychiatry2022

Adaptation and validation of the Chinese version of the Central Sensitisation Inventory in patients with chronic pain.

Dongfeng Liang, Xiangli Yu, Xiaojie Guo, Jie Zhang

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In one paragraph

Article in General psychiatry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 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

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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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

4 authors.

Dongfeng Liang *Department of Rheumatology and Immunology, First Medical Center of Chinese PLA General Hospital, Beijing, China.ORCID 0000-0002-9830-0225
Xiangli Yu *Outpatient Department, First Medical Center of Chinese PLA General Hospital, Beijing, China.
Xiaojie GuoDepartment of Psychology, First Medical Center of Chinese PLA General Hospital, Beijing, China.
Jie ZhangDepartment of Rheumatology and Immunology, First Medical Center of Chinese PLA General Hospital, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The 25-item Central Sensitisation Inventory (CSI-25) is a patient-reported instrument used to screen patients at risk of central sensitisation, a pathophysiological mechanism implicated in many chronic pain syndromes. Aims: To adapt and validate a Chinese version of the CSI-25 in the Chinese population. Methods: The Chinese CSI-25 was developed by the translation of the original English version, back translation, cultural adaptation and revision using the Delphi method. The Chinese CSI-25 was administered to 237 patients with chronic pain and 55 healthy controls. Structural validity (confirmatory factor analysis), construct validity (correlations with other instruments), test-retest reliability and internal consistency were evaluated. Results: Confirmatory factor analysis extracted four main factors ('physical symptoms', 'emotional distress', 'headache/jaw symptoms' and 'urological symptoms'). The Chinese CSI-25 score was positively correlated with the Pain Catastrophic Scale (PCS) total score (r=0.709), PCS subscale scores (r=0.630-0.695), Brief Pain Inventory (BPI) mean item score (r=0.773), BPI total score (r=0.773) and the number of painful sites (r=0.636). The Chinese CSI-25 had excellent test-retest reliability (intragroup correlation coefficient=0.975) and good internal consistency (Cronbach's α=0.930 in the overall population and 0.882 in the chronic pain population). Conclusions: The Chinese CSI-25 had excellent test-retest reliability and satisfactory structural validity and construct validity. This instrument could potentially be used in China as a self-report questionnaire in both clinical practice and research settings.

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Self ReportSurveys and Questionnaires

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PMID36654666
PMCPMC9791373

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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.