Identifying cutoff scores for the EORTC QLQ-C30 and the head and neck cancer-specific module EORTC QLQ-H&N35 representing unmet supportive care needs in patients with head and neck cancer

Head & Neck ◽  
2015 ◽  
Vol 38 (S1) ◽  
pp. E1493-E1500 ◽  
Author(s):  
Femke Jansen ◽  
Claire F. Snyder ◽  
C. René Leemans ◽  
Irma M. Verdonck-de Leeuw
2016 ◽  
Vol 24 (10) ◽  
pp. 4283-4291 ◽  
Author(s):  
Paul Hanly ◽  
Rebecca Maguire ◽  
Myles Balfe ◽  
Philip Hyland ◽  
Aileen Timmons ◽  
...  

2013 ◽  
Vol 69 (12) ◽  
pp. 2750-2758 ◽  
Author(s):  
Winnie K.W. So ◽  
K.C. Choi ◽  
Carmen W.H. Chan ◽  
Winnie P.Y. Tang ◽  
Alice W.Y. Leung ◽  
...  

2019 ◽  
Vol 42 (1) ◽  
pp. 67-78 ◽  
Author(s):  
Winnie K.W. So ◽  
Cho-Lee Wong ◽  
Kai-Chow Choi ◽  
Carmen W.H. Chan ◽  
Joanne C.Y. Chan ◽  
...  

2020 ◽  
Author(s):  
Jianxia LYU ◽  
Li Yin ◽  
Ping Cheng ◽  
Bin Li ◽  
Shanshan Peng ◽  
...  

Abstract Background: This study aimed to translate the English version of the supportive care needs scale of head and neck cancer patients (SCNS-HNC) questionnaire into Mandarin and to test the reliability and validity of the SCNS-SF34 and SCNS-HNC module in head and neck cancer patients. Methods: The Mandarin version of the Supportive Care Needs Survey Short-Form (SCNS-SF34) and SCNS-HNC scales were used to assess 206 patients with head and neck cancer in Chengdu, China. Among them, 51 patients were re-tested 2 or 3 days after the first survey. The internal consistency of the scale was evaluated by Cronbach's alpha coefficient, the retest reliability of the scale was evaluated by retest correlation coefficient r, the structural validity of the scale was evaluated by exploratory factor analysis, and the ceiling and floor effects of the scale were evaluated. Results: The Mandarin version of the SCNS-HNC had Cronbach's alpha coefficients greater than 0.700 (0.737 ≤ 0.962) for all of the domains. Except for the psychological demand dimension (r=0.674) of the SCNS-SF34 scale, the retest reliability of the other domains was greater than 0.8. Three common factors were extracted by exploratory factor analysis, and the cumulative variance contribution rate was 64.39%. Conclusions: The Mandarin version of the SCNS-SF34 and SCNS-HNC demonstrated satisfactory reliability and validity and is able to measure the supportive care needs of Chinese patients with head and neck cancer.


2016 ◽  
Vol 25 (11-12) ◽  
pp. 1576-1586 ◽  
Author(s):  
Myles Balfe ◽  
Katie O'Brien ◽  
Aileen Timmons ◽  
Phyllis Butow ◽  
Eleanor O' Sullivan ◽  
...  

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Jianxia Lyu ◽  
Li Yin ◽  
Ping Cheng ◽  
Bin Li ◽  
Shanshan Peng ◽  
...  

Abstract Background This study aimed to translate the English version of the supportive care needs scale of head and neck cancer patients (SCNS-HNC) questionnaire into Mandarin and to test the reliability and validity of the SCNS-SF34 and SCNS-HNC module in head and neck cancer patients. Methods The Mandarin version of the Supportive Care Needs Survey Short-Form (SCNS-SF34) and SCNS-HNC scales were used to assess 206 patients with head and neck cancer in Chengdu, China. Among them, 51 patients were re-tested 2 or 3 days after the first survey. The internal consistency of the scale was evaluated by Cronbach’s alpha coefficient, the retest reliability of the scale was evaluated by retest correlation coefficient r, the structural validity of the scale was evaluated by exploratory factor analysis, and the ceiling and floor effects of the scale were evaluated. Results The Mandarin version of the SCNS-HNC had Cronbach’s alpha coefficients greater than 0.700 (0.737 ≤ 0.962) for all of the domains. Except for the psychological demand dimension (r = 0.674) of the SCNS-SF34 scale, the retest reliability of the other domains was greater than 0.8. Three common factors were extracted by exploratory factor analysis, and the cumulative variance contribution rate was 64.39%. Conclusions The Mandarin version of the SCNS-SF34 and SCNS-HNC demonstrated satisfactory reliability and validity and is able to measure the supportive care needs of Chinese patients with head and neck cancer. Trial registration ChiCTR, ChiCTR1900026635. Registered 16 October 2019- Retrospectively registered.


2020 ◽  
Author(s):  
Jianxia LYU ◽  
Li Yin ◽  
Ping Cheng ◽  
Bin Li ◽  
Shanshan Peng ◽  
...  

Abstract Background To translate the English version of supportive care needs scale of head and neck cancer patients (SCNS-HNC) questionnaire into Mandarin (Simplified), and to test reliability and validity. Methods The With authorization of the English version scale were obtained from Professor Irma M. Verdonck-de Leeuw who worked at VU University Medical Center of Cancer Center Amsterdam (CCA), in the Netherlands. The Mandarin (Simplified) version of the SCNS-HNC scale was developed by translation, back-translation and cultural adaptation. The Mandarin (Simplified) version of Supportive Care Needs Survey Short-Form (SCNS-SF34) and SCNS-HNC scales were used to measure 206 patients with head and neck cancer in a upper first-class hospital in Chengdu. Among them, 51 patients were re-tested 2 or 3 days after the first survey. The internal consistency of the scale was evaluated by Cronbach's alpha coefficient, the retest reliability of the scale was evaluated by retest correlation coefficient r, the structural validity of the scale was evaluated by exploratory factor analysis, and the ceiling and floor effects of the scale were evaluated. Item-domain correlation analysis was used to evaluate the collective validity and differential validity of the scale. Results The Mandarin (Simplified) version of SCNS-HNC had Cronbach's alpha coefficients of more than 0.700 (0.737 ≤ 0.962)for the all of the domians. Except for the psychological demand dimension of SCNS-SF34 scale, the retest reliability in other fields was more than 0.8. Three common factors were extracted by exploratory factor analysis, and the cumulative variance contribution rate was 64.39%. The correlation coefficient of all items in Mandarin (Simplified) version of SCNS-SF34and SCNS-HNC with their own domians were higher than those with otherdomians. Conclusion The Mandarin (Simplified) of SCNS-HNC demonstrates satisfactory reliability and validity, which is available for measurement of the supportive care needs of Chinese patients with head and neck cancer.Clinical registration number: ChiCTR1900026635


2020 ◽  
Author(s):  
Jianxia LYU ◽  
Li Yin ◽  
Ping Cheng ◽  
Bin Li ◽  
Shanshan Peng ◽  
...  

Abstract Background: This study aimed to translate the English version of the supportive care needs scale of head and neck cancer patients (SCNS-HNC) questionnaire into Mandarin and to test its reliability and validity.Methods: The Mandarin version of the Supportive Care Needs Survey Short-Form (SCNS-SF34) and SCNS-HNC scales were used to assess 206 patients with head and neck cancer in Chengdu, China. Among them, 51 patients were re-tested 2 or 3 days after the first survey. The internal consistency of the scale was evaluated by Cronbach's alpha coefficient, the retest reliability of the scale was evaluated by retest correlation coefficient r, the structural validity of the scale was evaluated by exploratory factor analysis, and the ceiling and floor effects of the scale were evaluated.Results: The Mandarin version of the SCNS-HNC had Cronbach's alpha coefficients greater than 0.700 (0.737 ≤ 0.962) for all of the domains. Except for the psychological demand dimension (r=0.674) of the SCNS-SF34 scale, the retest reliability of the other domains was greater than 0.8. Three common factors were extracted by exploratory factor analysis, and the cumulative variance contribution rate was 64.39%. Conclusions: The Mandarin version of the SCNS-HNC demonstrated satisfactory reliability and validity and is able to measure the supportive care needs of Chinese patients with head and neck cancer.Clinical registration number: ChiCTR1900026635


Author(s):  
W.K.W. So ◽  
C.L. Wong ◽  
K.C. Choi ◽  
C.W.H. Chan ◽  
J.C.Y. Chan ◽  
...  

2020 ◽  
Vol 28 (11) ◽  
pp. 5557-5567 ◽  
Author(s):  
Melissa Henry ◽  
Ali Alias ◽  
Maria Cherba ◽  
Claudia Woronko ◽  
Zeev Rosberger ◽  
...  

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