The reliability, validity, and responsiveness of Cognitive Exercise Therapy Approach: Biopsychosocial Questionnaire for patients with psoriatic arthritis

The validity, reliability, and responsiveness of a new biopscyhosocial questionnaire for patients with systemic lupus erythematosus

OBJECTIVE

In recent years, the importance of holistic care in individuals with systemic lupus erythematosus (SLE) has been emphasized, and therefore a measurement tool that evaluates biopsychosocial impact is needed. This study was conducted to determine the validity, reliability, and responsiveness of the Cognitive Exercise Therapy Approach-Biopsychosocial Questionnaire (BETY-BQ) in individuals with SLE.

METHODS

Lupus Quality of Life (LupusQoL), Short Form-36 (SF-36), Health Assessment Questionnaire (HAQ), and Hospital Anxiety and Depression Scale (HADS) were used for the validity. For reliability, evaluations were repeated at 1 -week intervals and for responsiveness, the same scales were re-administered at 3-month intervals to 30 patients.

RESULTS

BETY-BQ showed moderate to high correlations with LupusQoL subparameters (rho = -0.522 to -0.718, p < 0.001), moderate to very high correlations with SF-36 subparameters (r = -0.826 to rho = 0.594, p < 0.001), high correlations with HAQ and HADS-D (rho = 0.735, p < 0.001; rho = 0.622, p < 0.001, respectively) and a moderate correlation with HADS-A (rho = 0.571, p < 0.001). In the test-retest method the correlation between the responses was very high (r = 0.989, p < 0.001). The intraclass correlation coefficient (r = 0.944, p < 0.001) and Cronbach's alpha value were found to be excellent (0.952). BETY-BQ showed moderate correlations with LupusQoL subparameters (the body image r = -0.443, p = 0.014; planning rho = -0.529, p = 0.003; fatigue r = -0.484, p = 0.007; intimate relationships rho = -0.421, p = 0.02), SF-36 social function subparameter (rho = -0.427, p = 0.019) and anxiety and depression subparameter of HADS (rho = 0.418, p = 0.021; r = 0.507, p = 0.004, respectively).

CONCLUSION

BETY-BQ which was found as a valid, reliable, and responsive scale in individuals with SLE, was presented to healthcare professionals for use in clinical and research studies as a scale that can be preferred in the evaluation of biopsychosocial status of individuals with SLE.

Reducing the question burden of patient reported outcome measures using Bayesian networks

Patient Reported Outcome Measures (PROMs) are questionnaires completed by patients about aspects of their health status. They are a vital part of learning health systems as they are the primary source of information about important outcomes that are best assessed by patients such as pain, disability, anxiety and depression. The volume of questions can easily become burdensome. Previous techniques reduced this burden by dynamically selecting questions from question item banks which are specifically built for different latent constructs being measured. These techniques analyzed the information function between each question in the item bank and the measured construct based on item response theory then used this information function to dynamically select questions by computerized adaptive testing. Here we extend those ideas by using Bayesian Networks (BNs) to enable Computerized Adaptive Testing (CAT) for efficient and accurate question selection on widely-used existing PROMs. BNs offer more comprehensive probabilistic models of the connections between different PROM questions, allowing the use of information theoretic techniques to select the most informative questions. We tested our methods using five clinical PROM datasets, demonstrating that answering a small subset of questions selected with CAT has similar predictions and error to answering all questions in the PROM BN. Our results show that answering 30% - 75% questions selected with CAT had an average area under the receiver operating characteristic curve (AUC) of 0.92 (min: 0.8 - max: 0.98) for predicting the measured constructs. BNs outperformed alternative CAT approaches with a 5% (min: 0.01% - max: 9%) average increase in the accuracy of predicting the responses to unanswered question items.