BACKGROUND: Increasing attention is being devoted to cognitive-behavioural measures to improve interventions for chronic pain. OBJECTIVE: To develop an Italian version of the Coping Strategies Questionnaire - Revised (CSQ-R), and to validate it in a study involving 345 Italian subjects with chronic pain. METHODS: The questionnaire was developed following international recommendations. The psychometric analyses included confirmatory factor analysis; reliability, assessed by internal consistency (Cronbach's alpha) and test-retest reliability (intraclass correlation coefficients); and construct validity, assessed by calculating the correlations between the subscales of the CSQ-R and measures of pain (numerical rating scale), disability (Sickness Impact Profile - Roland Scale), depression (Center for Epidemiological Studies - Depression Scale) and coping (Chronic Pain Coping Inventory) (Pearson's correlation). RESULTS: Confirmatory factor analysis revealed that the CSQ-R model had an acceptable data-model fit (comparative fit index and normed fit index ≥0.90, root mean square error of approximation ≤0.08). Cronbach's alpha was satisfactory (CSQ-R 0.914 to 0.961), and the intraclass correlation coefficients were good⁄excellent (CSQ-R 0.850 to 0.918). As expected, the correlations with the numerical rating scale, Sickness Impact Profile - Roland Scale, Center for Epidemiological Studies - Depression Scale and Chronic Pain Coping Inventory highlighted the adaptive and maladaptive properties of most of the CSQ-R subscales. CONCLUSION: The CSQ-R was successfully translated into Italian. The translation proved to have good factorial structure, and its psychometric properties are similar to those of the original and other adapted versions. Its use is recommended for clinical and research purposes in Italy and abroad.
BACKGROUND: Increasing attention is being devoted to cognitive-behavioural measures to improve interventions for chronic pain. OBJECTIVE: To develop an Italian version of the Coping Strategies Questionnaire - Revised (CSQ-R), and to validate it in a study involving 345 Italian subjects with chronic pain. METHODS: The questionnaire was developed following international recommendations. The psychometric analyses included confirmatory factor analysis; reliability, assessed by internal consistency (Cronbach's alpha) and test-retest reliability (intraclass correlation coefficients); and construct validity, assessed by calculating the correlations between the subscales of the CSQ-R and measures of pain (numerical rating scale), disability (Sickness Impact Profile - Roland Scale), depression (Center for Epidemiological Studies - Depression Scale) and coping (Chronic Pain Coping Inventory) (Pearson's correlation). RESULTS: Confirmatory factor analysis revealed that the CSQ-R model had an acceptable data-model fit (comparative fit index and normed fit index ≥0.90, root mean square error of approximation ≤0.08). Cronbach's alpha was satisfactory (CSQ-R 0.914 to 0.961), and the intraclass correlation coefficients were good⁄excellent (CSQ-R 0.850 to 0.918). As expected, the correlations with the numerical rating scale, Sickness Impact Profile - Roland Scale, Center for Epidemiological Studies - Depression Scale and Chronic Pain Coping Inventory highlighted the adaptive and maladaptive properties of most of the CSQ-R subscales. CONCLUSION: The CSQ-R was successfully translated into Italian. The translation proved to have good factorial structure, and its psychometric properties are similar to those of the original and other adapted versions. Its use is recommended for clinical and research purposes in Italy and abroad.
Authors: Marco Monticone; Simona Ferrante; Ines Giorgi; Caterina Galandra; Barbara Rocca; Calogero Foti Journal: Qual Life Res Date: 2012-09-27 Impact factor: 4.147
Authors: Jared J Tanner; Alisa J Johnson; Ellen L Terry; Josue Cardoso; Cynthia Garvan; Roland Staud; Georg Deutsch; Hrishikesh Deshpande; Song Lai; Adriana Addison; David Redden; Burel R Goodin; Catherine C Price; Roger B Fillingim; Kimberly T Sibille Journal: J Neurosci Res Date: 2021-02-19 Impact factor: 4.164
Authors: Alisa J Johnson; Ellen Terry; Emily J Bartley; Cynthia Garvan; Yenisel Cruz-Almeida; Burel Goodin; Toni L Glover; Roland Staud; Laurence A Bradley; Roger B Fillingim; Kimberly T Sibille Journal: Mol Pain Date: 2019 Jan-Dec Impact factor: 3.395
Authors: Teresa Paolucci; Alessandro de Sire; Martina Ferrillo; Dania di Fabio; Aurora Molluso; Antonia Patruno; Mirko Pesce; Carlo Lai; Chiara Ciacchella; Aristide Saggino; Francesco Agostini; Marco Tommasi Journal: Front Physiol Date: 2022-08-26 Impact factor: 4.755