Evaluation of the Paper and Smartphone Versions of the Quick Inventory of Depressive Symptomatology-Self-Report (QIDS-SR16) and the Patient Health Questionnaire-9 (PHQ-9) in Depressed Patients in China.

depressive disorder equivalence intraclass correlation coefficient questionnaires smartphone

Journal

Neuropsychiatric disease and treatment
ISSN: 1176-6328
Titre abrégé: Neuropsychiatr Dis Treat
Pays: New Zealand
ID NLM: 101240304

Informations de publication

Date de publication:
2020
Historique:
received: 10 12 2019
accepted: 24 03 2020
entrez: 6 5 2020
pubmed: 6 5 2020
medline: 6 5 2020
Statut: epublish

Résumé

Smartphone-based questionnaires have advantages compared with their paper versions, but there is a lack of consistent research on depressive disorder questionnaires. This study aimed to assess the equivalence between the paper and smartphone versions of the Quick Inventory of Depressive Symptomatology-Self-Report (QIDS-SR16) and Patient Health Questionnaire-9 (PHQ-9) for patients with depressive disorders in psychiatric hospitals in China. This was a randomized crossover study of 110 depressed patients recruited from the outpatient department of Beijing Anding Hospital from March 2016 to September 2018. Group 1 completed both the QIDS-SR16 and PHQ-9 in paper format and then completed the smartphone version 1-2 h later. Group 2 completed the scales in the reverse order. Reliability was evaluated using intraclass correlation coefficients (ICCs) with 95% confidence intervals (CI). The expected ICC was 0.9 (α=0.05). The overall ICC score of the QIDS-SR16 paper and smartphone versions was 0.904 (95% CI: 0.861-0.934), and the ICCs of each item ranged from 0.769 to 0.923. The overall ICC score of the PHQ-9 paper and smartphone versions was 0.951 (95% CI: 0.929-0.967), and the ICCs of each item ranged from 0.779 to 0.914. This study demonstrated the equivalence of the paper and smartphone versions of the PHQ-9 and QIDS-SR16 in depressed patients in China.

Identifiants

pubmed: 32368061
doi: 10.2147/NDT.S241766
pii: 241766
pmc: PMC7173799
doi:

Types de publication

Journal Article

Langues

eng

Pagination

993-1001

Informations de copyright

© 2020 Zhen et al.

Déclaration de conflit d'intérêts

The authors report no conflicts of interest in this work.

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Auteurs

Long Zhen (L)

The National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders and Beijing Anding Hospital, Capital Medical University, Beijing 100088, People's Republic of China.
Tianjin Mental Health Center, Tianjin Anding Hospital, Tianjin 300222, People's Republic of China.

Gang Wang (G)

The National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders and Beijing Anding Hospital, Capital Medical University, Beijing 100088, People's Republic of China.

Gailing Xu (G)

Tianjin Mental Health Center, Tianjin Anding Hospital, Tianjin 300222, People's Republic of China.

Le Xiao (L)

The National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders and Beijing Anding Hospital, Capital Medical University, Beijing 100088, People's Republic of China.

Lei Feng (L)

The National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders and Beijing Anding Hospital, Capital Medical University, Beijing 100088, People's Republic of China.

Xu Chen (X)

The National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders and Beijing Anding Hospital, Capital Medical University, Beijing 100088, People's Republic of China.

Man Liu (M)

The National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders and Beijing Anding Hospital, Capital Medical University, Beijing 100088, People's Republic of China.

Xuequan Zhu (X)

The National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders and Beijing Anding Hospital, Capital Medical University, Beijing 100088, People's Republic of China.

Classifications MeSH