Neuro-11: a new questionnaire for the assessment of somatic symptom disorder in general hospitals.

neuropsychiatry neuropsychological tests

Journal

General psychiatry
ISSN: 2517-729X
Titre abrégé: Gen Psychiatr
Pays: England
ID NLM: 101735271

Informations de publication

Date de publication:
2023
Historique:
received: 18 04 2023
accepted: 01 08 2023
medline: 4 9 2023
pubmed: 4 9 2023
entrez: 4 9 2023
Statut: epublish

Résumé

Somatic symptom disorder (SSD) commonly presents in general hospital settings, posing challenges for healthcare professionals lacking specialised psychiatric training. The Neuro-11 Neurosis Scale (Neuro-11) offers promise in screening and evaluating psychosomatic symptoms, comprising 11 concise items across three dimensions: somatic symptoms, negative emotions and adverse events. Prior research has validated the scale's reliability, validity and theoretical framework in somatoform disorders, indicating its potential as a valuable tool for SSD screening in general hospitals. This study aimed to establish the reliability, validity and threshold of the Neuro-11 by comparing it with standard questionnaires commonly used in general hospitals for assessing SSD. Through this comparative analysis, we aimed to validate the effectiveness and precision of the Neuro-11, enhancing its utility in clinical settings. Between November 2020 and December 2021, data were collected from 731 patients receiving outpatient and inpatient care at Shenzhen People's Hospital in China for various physical discomforts. The patients completed multiple questionnaires, including the Neuro-11, Short Form 36 Health Survey, Patient Health Questionnaire 15 items, Hamilton Anxiety Scale and Hamilton Depression Scale. Psychiatry-trained clinicians conducted structured interviews and clinical examinations to establish a gold standard diagnosis of SSD. The Neuro-11 demonstrated strong content reliability and structural consistency, correlating significantly with internationally recognised and widely used questionnaires. Despite its brevity, the Neuro-11 exhibited significant correlations with other questionnaires. A test-retest analysis yielded a correlation coefficient of 1.00, Spearman-Brown coefficient of 0.64 and Cronbach's α coefficient of 0.72, indicating robust content reliability and internal consistency. Confirmatory factor analysis confirmed the validity of the three-dimensional structure (p<0.001, comparative fit index=0.94, Tucker-Lewis index=0.92, root mean square error of approximation=0.06, standardised root mean square residual=0.04). The threshold of the Neuro-11 is set at 10 points based on the maximum Youden's index from the receiver operating characteristic curve analysis. In terms of diagnostic efficacy, the Neuro-11 has an area under the curve of 0.67. (1) The Neuro-11 demonstrates robust associations with standard questionnaires, supporting its validity. It is applicable in general hospital settings, assessing somatic symptoms, negative emotions and adverse events. (2) The Neuro-11 exhibits strong content reliability and validity, accurately capturing the intended constructs. The three-dimensional structure demonstrates robust construct validity. (3) The threshold of the Neuro-11 is set at 10 points.

Sections du résumé

Background UNASSIGNED
Somatic symptom disorder (SSD) commonly presents in general hospital settings, posing challenges for healthcare professionals lacking specialised psychiatric training. The Neuro-11 Neurosis Scale (Neuro-11) offers promise in screening and evaluating psychosomatic symptoms, comprising 11 concise items across three dimensions: somatic symptoms, negative emotions and adverse events. Prior research has validated the scale's reliability, validity and theoretical framework in somatoform disorders, indicating its potential as a valuable tool for SSD screening in general hospitals.
Aims UNASSIGNED
This study aimed to establish the reliability, validity and threshold of the Neuro-11 by comparing it with standard questionnaires commonly used in general hospitals for assessing SSD. Through this comparative analysis, we aimed to validate the effectiveness and precision of the Neuro-11, enhancing its utility in clinical settings.
Methods UNASSIGNED
Between November 2020 and December 2021, data were collected from 731 patients receiving outpatient and inpatient care at Shenzhen People's Hospital in China for various physical discomforts. The patients completed multiple questionnaires, including the Neuro-11, Short Form 36 Health Survey, Patient Health Questionnaire 15 items, Hamilton Anxiety Scale and Hamilton Depression Scale. Psychiatry-trained clinicians conducted structured interviews and clinical examinations to establish a gold standard diagnosis of SSD.
Results UNASSIGNED
The Neuro-11 demonstrated strong content reliability and structural consistency, correlating significantly with internationally recognised and widely used questionnaires. Despite its brevity, the Neuro-11 exhibited significant correlations with other questionnaires. A test-retest analysis yielded a correlation coefficient of 1.00, Spearman-Brown coefficient of 0.64 and Cronbach's α coefficient of 0.72, indicating robust content reliability and internal consistency. Confirmatory factor analysis confirmed the validity of the three-dimensional structure (p<0.001, comparative fit index=0.94, Tucker-Lewis index=0.92, root mean square error of approximation=0.06, standardised root mean square residual=0.04). The threshold of the Neuro-11 is set at 10 points based on the maximum Youden's index from the receiver operating characteristic curve analysis. In terms of diagnostic efficacy, the Neuro-11 has an area under the curve of 0.67.
Conclusions UNASSIGNED
(1) The Neuro-11 demonstrates robust associations with standard questionnaires, supporting its validity. It is applicable in general hospital settings, assessing somatic symptoms, negative emotions and adverse events. (2) The Neuro-11 exhibits strong content reliability and validity, accurately capturing the intended constructs. The three-dimensional structure demonstrates robust construct validity. (3) The threshold of the Neuro-11 is set at 10 points.

Identifiants

pubmed: 37663052
doi: 10.1136/gpsych-2023-101082
pii: gpsych-2023-101082
pmc: PMC10471855
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e101082

Informations de copyright

© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Déclaration de conflit d'intérêts

Competing interests: None declared.

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Auteurs

Silin Zeng (S)

Department of Neurology, Shenzhen People's Hospital,The second Affiliated Hospitals of Jinan University, The first Affiliated Hospitals of Southern University of Science and Technology, Shenzhen, Guangdong, China.
Jinan University, Guangzhou, Guangdong, China.

Yian Yu (Y)

Department of Statistics and Data Science, Southern University of Science and Technology, Shenzhen, Guangdong, China.

Shan Lu (S)

Institute of Neurological Diseases, Shenzhen Bay Laboratory, Shenzhen, Guangdong, China.

Sirui Zhang (S)

Department of Neurology, Shenzhen People's Hospital,The second Affiliated Hospitals of Jinan University, The first Affiliated Hospitals of Southern University of Science and Technology, Shenzhen, Guangdong, China.

Xiaolin Su (X)

Department of Neurology, Shenzhen People's Hospital,The second Affiliated Hospitals of Jinan University, The first Affiliated Hospitals of Southern University of Science and Technology, Shenzhen, Guangdong, China.

Ge Dang (G)

Department of Neurology, Shenzhen People's Hospital,The second Affiliated Hospitals of Jinan University, The first Affiliated Hospitals of Southern University of Science and Technology, Shenzhen, Guangdong, China.

Ying Liu (Y)

Department of neurology, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.

Zhili Cai (Z)

Department of Neurology, Shenzhen People's Hospital,The second Affiliated Hospitals of Jinan University, The first Affiliated Hospitals of Southern University of Science and Technology, Shenzhen, Guangdong, China.

Siyan Chen (S)

Department of Neurology, Shenzhen People's Hospital,The second Affiliated Hospitals of Jinan University, The first Affiliated Hospitals of Southern University of Science and Technology, Shenzhen, Guangdong, China.

Yitao He (Y)

Department of Neurology, Shenzhen People's Hospital,The second Affiliated Hospitals of Jinan University, The first Affiliated Hospitals of Southern University of Science and Technology, Shenzhen, Guangdong, China.

Xin Jiang (X)

Department of Geriatrics, Shenzhen People's Hospital,The second Affiliated Hospitals of Jinan University, The first Affiliated Hospitals of Southern University of Science and Technology, Shenzhen, China.

Chanjuan Chen (C)

Department of Neurology, Shenzhen People's Hospital,The second Affiliated Hospitals of Jinan University, The first Affiliated Hospitals of Southern University of Science and Technology, Shenzhen, Guangdong, China.

Lei Yuan (L)

Department of Neurology, Shenzhen People's Hospital,The second Affiliated Hospitals of Jinan University, The first Affiliated Hospitals of Southern University of Science and Technology, Shenzhen, Guangdong, China.

Peng Xie (P)

NHC Key Laboratory of Diagnosis and Treatment on First Affiliated Hospital of Chongqing Medical University, Chongqing, Chongqing, China.

Jianqing Shi (J)

Department of Statistics and Data Science, Southern University of Science and Technology, Shenzhen, Guangdong, China.
National Center for Applied Mathematics, Shenzhen, Guangdong, China.

Qingshan Geng (Q)

Department of Geriatrics, Shenzhen People's Hospital,The second Affiliated Hospitals of Jinan University, The first Affiliated Hospitals of Southern University of Science and Technology, Shenzhen, China.

Rafael H Llinas (RH)

Department of neurology, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.

Yi Guo (Y)

Department of Neurology, Shenzhen People's Hospital,The second Affiliated Hospitals of Jinan University, The first Affiliated Hospitals of Southern University of Science and Technology, Shenzhen, Guangdong, China.
Institute of Neurological Diseases, Shenzhen Bay Laboratory, Shenzhen, Guangdong, China.

Classifications MeSH