Introduction: Temporomandibular Joint Dysfunction (TMD) encompasses a variety of disorders affecting the Temporomandibular Joint (TMJ) and associated muscles. These conditions can significantly impact an individual’s quality of life, causing pain, limited jaw movement, and difficulties in daily functional activities. Myofascial TMD, characterised by muscle pain and tenderness, is one of the most common forms of this disorder. Existing treatment methods often include exercise techniques aimed at reducing pain and improving jaw function. Need for the Study: The Strain Counterstrain Technique (SCT) has the potential to provide a patient centered, non invasive, and holistic approach to resolving the issues associated with these complex conditions. Further research into this technique is necessary for addressing TMJ disorders. This research will enhance the scientific understanding of its effectiveness and, consequently, improve treatment outcomes and management strategies for TMJ diseases in general. To enhance our understanding and patient outcomes, it is imperative to examine the Strain Counterstrain approach in TMJ disorders. Aim: To evaluate and compare the effectiveness of three different exercise techniques in treating myofascial TMD: Ischaemic Compression Technique (ICT), SCT, and conventional exercises. Materials and Methods: A Randomised Controlled Trial (RCT) will be conducted at Acharya Vinoba Bhave Rural Hospital from February 2024 to June 2025. The study will include individuals aged 18 to 65 with a confirmed diagnosis of myofascial TMD. Thirty participants will be randomly assigned to each of the three treatment groups (ICT, SCT, and Conventional Exercises), comprising a total sample size of 90. The parameters to be assessed include pain levels using the Numerical Pain Rating Scale (NPRS); active mouth opening, measured with a mandibular goniometer; and functional activities, assessed using the Jaw Functional Limitation Scale (JFLS). Continuous outcome variables will be examined using normality tests and summarised using descriptive statistics. Significance will be determined using ANOVA tests for normally distributed data and Kruskal-Wallis tests for non-normally distributed data. Categorical variables will be summarised by frequency and percentage, and Chi-square tests will be used to measure efficacy. A p-value of <0.05 will be considered significant.
Deshmukh et al. (Tue,) studied this question.