Abstract

Introduction“Dizziness” is a common complaint in clinical practice that can occur with anyone. However, since the symptom is caused by a wide range of disorders, a general clinician usually faces some difficulty to detect the cause. ObjectiveThis study aimed to formulate and validate a simple instrument that can be used to screen and predict the most likely cause of dizziness in Thai outpatients. MethodsThis study was divided into two phases. Phase I included 41 patients diagnosed with common causes of dizziness to determine the algorithm and construct the “structural algorithm questionnaire version 1”. In addition, to test and retest its content validity and reliability until the instrument had an acceptable level of both. Phase II of the study pertained to evaluating its accuracy in clinical trials, 150 patients with dizziness had a face-to-face interview while they were waiting for their medical appointment. ResultsThe degree of agreement between the algorithm results and clinical diagnoses was within an acceptable level (κ = 0.69). Therefore, this algorithm was used to construct the structural algorithm questionnaire version 1. The content validity of the structural algorithm questionnaire version 1 evaluated by seven experts. The content validity index values of the questionnaire ranged from 0.71 to 1.0. The Cohen’s kappa coefficient (κ) of intra-rater reliability of the structural algorithm questionnaire version 1 was 0.71. In clinical trials, 150 patients with dizziness had a face-to-face interview while they were waiting for their appointment. The overall agreement between their questionnaire responses and final diagnoses by specialists showed a moderate degree of clinical accuracy (κ = 0.55). ConclusionsThe structural algorithm questionnaire version 1 had a well-developed design and acceptable quality pertaining to both validity and reliability. It might be used to differentiate the cause of dizziness between vestibular and non-vestibular disorders, especially of outpatients with dizziness symptoms.

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