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Objective <p>The<!--Query ID="Q1" Text="Please check and confirm if the authors and their respective affiliations have been correctly identified. Amend if necessary." Resolved="yes"--> quality of life(QoL) of patients with chronic diseases is a greater concern for both patients and clinicians. This study was aimed to develop and evaluate the second version of the General Module of Quality of Life Instruments for Chronic Diseases (QLICD-GM(V2.0)) by Classical Test Theory (CTT) and Item Response Theory (IRT) .</p> Methods <p>Building upon QLICD-GM(V1.0), the scale was developed and validated through a structured process combining qualitative and quantitative methods. The psychometric properties of QLICD-GM(V2.0) were assessed in a sample of 1953 patients with ten chronic diseases, evaluating reliability, validity, responsiveness, and item characteristics under CTT and IRT frameworks.</p> Results <p>The final QLICD-GM(V2.0) comprises 28 items across 3 domains and 9 facets. Item-domain correlations were highest for each item within its intended domain, except one. Confirmatory factor analysis indicated good model fit. Criterion validity against SF-36 showed correlations of 0.56 (physical), 0.54 (psychological), and 0.46 (social). Internal consistency was high (Cronbach’s α: 0.79–0.98). Significant pre- to post-treatment score differences were found (all <i>p</i> &lt; 0.001), with standardized response means of 0.24 (physical), 0.17 (psychological), and 0.07 (social). IRT analysis indicated all items had discrimination parameters between 1.11 and 1.41, with monotonically increasing location parameters. Average item information amount was approximately 0.33 (physical), 0.54 (psychological), and 0.44(social).</p> Conclusions <p>QLICD-GM(V2.0) provides a psychometrically sound, clinically interpretable and responsive measure of generic QoL in chronic patients. It can be used alone or combined with disease-specific modules to monitor benefit and guide treatment and rehabilitation planning.</p>

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Development and validation of the general module of the quality of life instruments for chronic diseases QLICD-GM(V2.0) : a large sample study based on classical test theory and item response theory

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年2月7日

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  • Chonghua Wan,
  • Xiaoqing Zhang,
  • Liyuan Qiao,
  • Wu Li,
  • Ying Chen,
  • Wanrui Ma,
  • Honghong Xue,
  • Peng Quan,
  • Dandan Wang

摘要

Objective

The quality of life(QoL) of patients with chronic diseases is a greater concern for both patients and clinicians. This study was aimed to develop and evaluate the second version of the General Module of Quality of Life Instruments for Chronic Diseases (QLICD-GM(V2.0)) by Classical Test Theory (CTT) and Item Response Theory (IRT) .

Methods

Building upon QLICD-GM(V1.0), the scale was developed and validated through a structured process combining qualitative and quantitative methods. The psychometric properties of QLICD-GM(V2.0) were assessed in a sample of 1953 patients with ten chronic diseases, evaluating reliability, validity, responsiveness, and item characteristics under CTT and IRT frameworks.

Results

The final QLICD-GM(V2.0) comprises 28 items across 3 domains and 9 facets. Item-domain correlations were highest for each item within its intended domain, except one. Confirmatory factor analysis indicated good model fit. Criterion validity against SF-36 showed correlations of 0.56 (physical), 0.54 (psychological), and 0.46 (social). Internal consistency was high (Cronbach’s α: 0.79–0.98). Significant pre- to post-treatment score differences were found (all p < 0.001), with standardized response means of 0.24 (physical), 0.17 (psychological), and 0.07 (social). IRT analysis indicated all items had discrimination parameters between 1.11 and 1.41, with monotonically increasing location parameters. Average item information amount was approximately 0.33 (physical), 0.54 (psychological), and 0.44(social).

Conclusions

QLICD-GM(V2.0) provides a psychometrically sound, clinically interpretable and responsive measure of generic QoL in chronic patients. It can be used alone or combined with disease-specific modules to monitor benefit and guide treatment and rehabilitation planning.