Current strength and conditioning in Southeast Asia: Practices,challenges,and emerging trends

Abstract

Strength and conditioning (S&C) is a field within exercise science that advocates evidence-based practice. As empirical knowledge evolves, translation of this knowledge into coaching practice is expected. However, knowledge translation remains challenging across many industries, particularly S&C, due to varying professional standards and limited resources. This study investigated current practices, challenges, and trends among S&C coaches in Southeast Asia (SEA). Seventy-one S&C coaches (87% male) from major sports organisations completed an online survey covering demographics, job satisfaction, motivation, programming knowledge, AI use, training principles, and exercise methods. Frequency analysis and Chi-square tests assessed data distribution and group differences. Most coaches held a bachelor's degree (93%) and S&C certification(s) (73%). Approximately half (49%) were satisfied with their roles, with mixed views on salary (38% satisfied vs. 38% dissatisfied). Passion (89%) was the primary motivator, while limited facilities (72%) and financial incentives (61%) were common challenges. Coaches reported greater proficiency in strength (87%) than conditioning (57%) programming. AI use within programming (e.g., ChatGPT) was limited (8%). Exercise selection was guided by training goals (93%), experience (87%), specificity (85%), and periodisation (80%). Load intensity and progression were primarily prescribed using percent-based (80% and 85%, respectively) and RPE-based (80%, 72%), with lower use of velocity-based methods (48%, 34%). Application of conventional, eccentric-, concentric-, and isometric-emphasis training were widespread (≥85%), with 100% using supersets for strength and hypertrophy development. S&C coaches in SEA demonstrated foundational qualifications, programming skills, and awareness of evidence-based methods, while emphasising athlete-centred approaches and communication. Structured professional development, consideration of AI-based tools, and organisational support are recommended.