Khon Kaen Universiry, Research Center in Back, Neck, Other Joint Pain and Human Performance (BNOJPH), Khon Kaen, Thailand; Khon Kaen University, Faculty of Associated Medical Sciences, School of Physical Therapy, Khon Kaen, Thailand.
Khon Kaen Universiry, Research Center in Back, Neck, Other Joint Pain and Human Performance (BNOJPH), Khon Kaen, Thailand; Khon Kaen University, Faculty of Associated Medical Sciences, School of Physical Therapy, Khon Kaen, Thailand.
Braz J Otorhinolaryngol. 2022 Sep-Oct;88(5):780-786. doi: 10.1016/j.bjorl.2021.05.007. Epub 2021 May 28.
"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.
This 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.
This 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.
The 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).
The 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.
“头晕”是临床实践中常见的主诉，任何人都可能出现。然而，由于引起头晕的病因广泛，一般临床医生通常难以确定病因。
本研究旨在制定和验证一种简单的工具，用于筛查和预测泰国门诊患者头晕的最可能病因。
本研究分为两个阶段。第 1 阶段纳入 41 例常见头晕病因的患者，以确定算法并构建“结构算法问卷 1 版”。此外，还对其内容效度和信度进行测试和再测试，直到仪器达到可接受的水平。第 2 阶段研究评估其在临床试验中的准确性，150 例头晕患者在等待就诊时进行面对面访谈。
算法结果与临床诊断的一致性在可接受水平内（κ=0.69）。因此，该算法被用于构建结构算法问卷 1 版。7 位专家评估结构算法问卷 1 的内容效度。问卷的内容效度指数值为 0.71-1.0。结构算法问卷 1 的内部信度的 Cohen's kappa 系数（κ）为 0.71。在临床试验中，150 例头晕患者在等待就诊时进行面对面访谈。他们的问卷回答与专家的最终诊断之间的总体一致性显示出中度临床准确性（κ=0.55）。
结构算法问卷 1 具有良好的设计，在有效性和可靠性方面具有可接受的质量。它可能用于区分前庭和非前庭疾病引起的头晕病因，特别是头晕症状的门诊患者。
