Development and Validation of a Short-Form Suboptimal Health Status Questionnaire

Author:

Sun Shuyu1,Liu Hongzhi1,Zheng Guo2,Guan Qihua1,Wang Yinghao1,Wang Jie1,Qi Yan3,Yan Yuxiang4,Wang Youxin4,Wen Jun5,Hou Haifeng1ORCID

Affiliation:

1. Shandong First Medical University

2. Vanderbilt University Medical Center

3. Yunnan Medical Health College

4. Capital Medical University

5. Edith Cowan University

Abstract

Abstract Background Suboptimal health status (SHS) is a reversible, borderline state between optimal health and disease. Although this condition’s definition is widely understood, related questionnaires must be developed to identify individuals with SHS in various populations relative to predictive, preventive, and personalized medicine (PPPM/3PM). This study presents a short-form suboptimal health status questionnaire (the SHSQ-SF) that appears to possess sufficient reliability and validity to assess SHS in large-scale populations. Methods A total of 6,183 participants enrolled from southern China constituted a training set, while 4,113 participants from northern China constituted an external validation set. The SHSQ-SF includes nine key items from the Suboptimal Health Status Questionnaire-25 (SHSQ-25), an instrument that has been applied in Caucasians, Asians, and Africans. Item analysis and reliability and validity tests were carried out to validate the SHSQ-SF. The receiver operating characteristic (ROC) curve was used to identify an optimal cutoff value for SHS diagnosis. Results The Cronbach’s α coefficient for the training dataset was 0.902; the split-half reliability was 0.863. The Kaiser–Meyer–Olkin (KMO) value was 0.880, and Bartlett’s test of sphericity was significant (χ2 = 32,929.680, p < 0.05). Both Kaiser’s criteria (eigenvalues > 1) and the scree plot revealed one factor explaining 57.008% of the total variance. Standardized factor loadings for the confirmatory factor analysis (CFA) indices ranged between 0.59 and 0.74, with χ2/ = 4.972, GFI = 0.996, CFI = 0.996, RFI = 0.989, and RMSEA = 0.031. The area under the ROC curve (AUC) was equal to 0.985 (95% CI: 0.983–0.988) for the training dataset. A cutoff value (≥ 11) was then identified for SHS diagnosis. The SHSQ-SF showed good discriminatory power for the external validation dataset (AUC = 0.975, 95% CI: 0.971–0.979) with a sensitivity of 96.2% and a specificity of 87.4%. Conclusions We developed a short form of the SHS questionnaire that demonstrated sound reliability and validity when assessing SHS in Chinese residents. From a PPPM/3PM perspective, the SHSQ-SF is recommended for rapid screening of individuals with SHS in large-scale populations.

Publisher

Research Square Platform LLC

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